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    Creating a Manhattan plot

    +

    Controlling the aesthetics (colours, point shapes, labels) of the +tracks +

    +

    The default look of the different data types (GWAS peaks, DE genes +and candidate genes) in a HIDECAN plots is controlled by the arguments +returned by hidecan_aes(). More specifically, the function +controls:

    +
      +
    • the label of each data type on the x-axis (e.g. ‘GWAS peaks’ for +GWAS results),

    • +
    • the colour of the vertical lines used to showcase the position of +markers or genes,

    • +
    • the shape of the points,

    • +
    • whether the name of the markers/genes are displayed (by default, +will only show for candidate genes),

    • +
    • the colour palette used for the score or log2 fold-change of the +points.

    • +
    +

    The default values used for these parameters have been chosen to +ensure that the resulting plot is easily understandable. However, it is +possible to change them. To do so, we’ll start by saving the defaults +returned by hidecan_aes():

    +
    +default_aes <- hidecan_aes()
    +
    +str(default_aes, max.level = 1)
    +#> List of 4
    +#>  $ GWAS_data_thr  :List of 5
    +#>  $ DE_data_thr    :List of 5
    +#>  $ CAN_data_thr   :List of 5
    +#>  $ CUSTOM_data_thr:List of 5
    +
    +default_aes[[1]]
    +#> $y_label
    +#> [1] "GWAS peaks"
    +#> 
    +#> $line_colour
    +#> [1] "red"
    +#> 
    +#> $point_shape
    +#> [1] 21
    +#> 
    +#> $show_name
    +#> [1] FALSE
    +#> 
    +#> $fill_scale
    +#> <ScaleContinuous>
    +#>  Range:  
    +#>  Limits:    0 --    1
    +

    As we can see above, the function returns a list of the default +aesthetics to use for GWAS results (the GWAS_data_thr +element), for DE results (DE_data_thr element), for +candidate genes (CAN_data_thr element), and for custom +tracks (CUSTOM_data_thr element - see the Adding custom tracks article for +more information). Each element is itself a list, containing the value +for each attribute mentioned above.

    +

    Let’s modify the label given to the GWAS peaks, and the colour +palette used for DE score:

    +
    +library(viridis)
    +
    +default_aes$GWAS_data_thr$y_label <- "GWAS signif. markers"
    +
    +default_aes$DE_data_thr$fill_scale <- scale_fill_viridis(
    +  "DE gene score",
    +  option = "inferno",
    +  guide = ggplot2::guide_colourbar(
    +    title.position = "top",
    +    title.hjust = 0.5,
    +    order = 3 # ensures this legend is shown after the one for GWAS scores
    +  )
    +)
    +

    We can use these modified values by passing this list to +hidecan_plot() through its custom_aes +argument:

    +
    +hidecan_plot(
    +  gwas_list = x[["GWAS"]],
    +  de_list = x[["DE"]],
    +  can_list = x[["CAN"]],     
    +  score_thr_gwas = -log10(0.0001),
    +  score_thr_de = -log10(0.05),
    +  log2fc_thr = 0,
    +  custom_aes = default_aes
    +)
    +

    +
    +

    Viewport error

    If you are working on RStudio, you may encounter the following @@ -549,7 +638,7 @@

    Viewport errorggplot2::ggsave() to save it into a file:

    -
    +
     p <- hidecan_plot(
       gwas_list = x[["GWAS"]],
       de_list = x[["DE"]],
    @@ -573,7 +662,7 @@ 

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  2. @@ -41,7 +42,9 @@

    All vignettes

    -
    HIDECAN plot from GWASpoly output
    +
    Adding custom tracks
    +
    +
    HIDECAN plot from GWASpoly output
    Creating a HIDECAN plot step by step
    @@ -58,7 +61,7 @@

    All vignettes

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    diff --git a/articles/web_only/custom_tracks.html b/articles/web_only/custom_tracks.html new file mode 100644 index 0000000..675f456 --- /dev/null +++ b/articles/web_only/custom_tracks.html @@ -0,0 +1,318 @@ + + + + + + + +Adding custom tracks • hidecan + + + + + + + + + + + + + + Skip to contents + + +
    + + + + +
    +
    + + + + +

    While hidecan was designed with the goal of representing GWAS and DE +results with lists of candidate genes, in principle it can be used to +visualise any genomic feature that can be mapped to a physical location +on the genome; for example significant QTLs, HiC data etc. To facilitate +this, it is possible to add one or more custom data types into a hidecan +plot.

    +
    +

    Adding one custom data type +

    +

    Let us start by simulating a new set of results – for simplicity +we’ll assume that we have results from a QTL mapping on the same markers +that were used for the GWAS analysis:

    +
    +x <- get_example_data()
    +
    +set.seed(586)
    +x$QTL <- x$GWAS |> 
    +  ## shuffling the scores around to get different "significant" markers
    +  mutate(score = sample(score, n(), replace = FALSE))
    +

    We can add this new data to the hidecan plot through the +custom_list argument of the hidecan_plot() +function (we’ll only look at two chromosomes for simplicity), and use +the score_thr_custom argument to set the significance +threshold on the score:

    +
    +hidecan_plot(
    +  gwas_list = x[["GWAS"]],
    +  score_thr_gwas = -log10(0.0001),
    +  chroms = c("ST4.03ch01", "ST4.03ch02"),
    +  custom_list = x[["QTL"]],
    +  score_thr_custom = -log10(0.0001)
    +)
    +

    +

    Importantly, the data-frame that is passed to +custom_list must contain at least the following columns: +chromosome, position and score. +If the genomic features you want to add are genes for example (with a +start and end position) you need to calculate the position +column yourself.

    +

    We can customise the labels and colours used for this custom track +with the help of the hidecan_aes() function:

    +
    +plot_aes <- hidecan_aes()
    +
    +str(plot_aes, max.level = 1)
    +#> List of 4
    +#>  $ GWAS_data_thr  :List of 5
    +#>  $ DE_data_thr    :List of 5
    +#>  $ CAN_data_thr   :List of 5
    +#>  $ CUSTOM_data_thr:List of 5
    +
    +plot_aes[["CUSTOM_data_thr"]]
    +#> $y_label
    +#> [1] "Custom track"
    +#> 
    +#> $line_colour
    +#> [1] "darkgoldenrod2"
    +#> 
    +#> $point_shape
    +#> [1] 21
    +#> 
    +#> $show_name
    +#> [1] FALSE
    +#> 
    +#> $fill_scale
    +#> <ScaleContinuous>
    +#>  Range:  
    +#>  Limits:    0 --    1
    +

    In particular, we will change the name given to the track, as well as +the name used for the legend:

    +
    +plot_aes$CUSTOM_data_thr$y_label <- "Signif. QTLs"
    +
    +plot_aes$CUSTOM_data_thr$fill_scale$name <- "QTL score"
    +
    +# We could also change the entire legend with:
    +
    +# default_aes$CUSTOM_data_thr$fill_scale <- scale_fill_viridis(
    +#   "QTL score",
    +#   option = "inferno",
    +#   guide = guide_colourbar(
    +#     title.position = "top",
    +#     title.hjust = 0.5,
    +#     order = 4 # ensures this legend is shown after the one for DE scores
    +#   )
    +# )
    +

    We will use these values in the hidecan plot by passing the list +through the custom_aes argument:

    +
    +hidecan_plot(
    +  gwas_list = x[["GWAS"]],
    +  score_thr_gwas = -log10(0.0001),
    +  chroms = c("ST4.03ch01", "ST4.03ch02"),
    +  custom_list = x[["QTL"]],
    +  score_thr_custom = -log10(0.0001),
    +  custom_aes = plot_aes
    +)
    +

    +

    Note that, as for the other supported data types, we can pass more +than one data-frame to custom_list to get several tracks of +QTLs:

    +
    +## Simulating a second set of QTL results
    +set.seed(779)
    +x$QTL2 <- x$QTL |> 
    +  mutate(score = sample(score, n(), replace = FALSE))
    +
    +hidecan_plot(
    +  gwas_list = x[["GWAS"]],    
    +  score_thr_gwas = -log10(0.0001),
    +  score_thr_de = -log10(0.05),
    +  log2fc_thr = 0,
    +  chroms = c("ST4.03ch01", "ST4.03ch02"),
    +  custom_list = list("Trait 1" = x[["QTL"]],
    +                     "Trait 2" = x[["QTL2"]]),
    +  score_thr_custom = -log10(0.0001),
    +  custom_aes = plot_aes
    +)
    +

    +

    By default, the values in the score column are shown as +the points colour, but we can hide it by setting the +fill_scale element of our aesthetics list to +NULL. Also, we can add labels to the significant points, by +adding a name column to the data-frame, and setting the +show_name element of our aesthetics list to +TRUE:

    +
    +## Creating fake names for the markers
    +set.seed(342)
    +x$QTL <- x$QTL |> 
    +  mutate(name = sample(LETTERS, n(), replace = TRUE))
    +
    +plot_aes2 <- plot_aes
    +
    +plot_aes2$CUSTOM_data_thr$show_name <- TRUE
    +plot_aes2$CUSTOM_data_thr$fill_scale <- NULL
    +
    +hidecan_plot(
    +  gwas_list = x[["GWAS"]],
    +  score_thr_gwas = -log10(0.0001),
    +  chroms = c("ST4.03ch01", "ST4.03ch02"),
    +  custom_list = x[["QTL"]],
    +  score_thr_custom = -log10(0.0001),
    +  custom_aes = plot_aes2
    +)
    +

    +
    +
    +

    Adding several custom data types +

    +

    It is also possible to add more than one custom data type. For +example, let’s say that we want to add information about differentially +methylated regions to the plot. We’ll use the example DE data to +simulate our methylated dataset:

    +
    +set.seed(554)
    +x$METH <- x$DE |> 
    +  mutate(
    +    position = (start + end) / 2, ## need to calculate the position of the regions
    +    score = sample(-log10(padj), n(), replace = FALSE),
    +    name = sample(letters, n(), replace = TRUE)
    +  )
    +

    Importantly, the significance threshold encoded by the +score_thr_custom argument of hidecan_plot() +will be used for all custom datasets, so if we don’t want to use the +same significance threshold on our QTL and methylation data, we need to +perform the filtering of significant features by hand before and then +set the threshold to 0:

    +
    +x$QTL <- x$QTL |> 
    +  filter(score >= -log10(0.0001))
    +
    +x$METH <- x$METH |> 
    +  filter(score >= -log10(0.04))
    +

    The key to specifying that the two custom datasets are different data +types is to add to the new data-frame an argument called +aes_type, which is simply a label that tells the function +which aesthetics settings it should use from the list passsed to +custom_aes. We will retain the aesthetics we have set for +the QTL scores, and create new aesthetics for the methylation data:

    +
    +## Adding the aes_type attribute to the methylation data
    +attr(x$METH, "aes_type") <- "METH"
    +
    +## The name of the new element in the aesthetics list must match the value of
    +## the aes_type attribute
    +plot_aes$METH <- list(
    +  y_label = "DMRs",
    +  line_colour = "purple",
    +  point_shape = 24,
    +  show_name = TRUE,
    +  fill_scale = scale_fill_viridis(
    +    "DM score",
    +    option = "mako",
    +    guide = guide_colourbar(
    +      title.position = "top",
    +      title.hjust = 0.5,
    +      order = 5
    +    )
    +  )
    +)
    +
    +hidecan_plot(
    +  gwas_list = x[["GWAS"]],
    +  score_thr_gwas = -log10(0.0001),
    +  chroms = c("ST4.03ch01", "ST4.03ch02"),
    +  custom_list = list(x[["QTL"]], x[["METH"]]),
    +  score_thr_custom = 0, ## no filtering, has been done manually
    +  custom_aes = plot_aes
    +)
    +

    +

    There are no restrictions on the number of custom data types that can +be added to a hidecan plot.

    +
    +
    +
    + + + +
    + + + +
    +
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    @@ -275,7 +276,7 @@

    Appendix: reproducing th

    diff --git a/articles/web_only/shiny-app.html b/articles/web_only/shiny-app.html index 3df2a44..8b292d0 100644 --- a/articles/web_only/shiny-app.html +++ b/articles/web_only/shiny-app.html @@ -42,6 +42,7 @@ @@ -92,7 +93,7 @@ diff --git a/authors.html b/authors.html index 2e26fcb..64cb243 100644 --- a/authors.html +++ b/authors.html @@ -21,6 +21,7 @@ @@ -72,7 +73,7 @@

    Citation

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    Developers

    diff --git a/news/index.html b/news/index.html index 8cdea7b..aa6d968 100644 --- a/news/index.html +++ b/news/index.html @@ -21,6 +21,7 @@ @@ -42,7 +43,13 @@

    hidecan 1.1.0.9000

    • Added the manhattan_plot() function to generate Manhattan plots from a table of GWAS results.

    • Fixed bug where specifying chromosome limits for hidecan_plot_from_gwaspoly() would mess up the ordering of the chromosomes in the plot.

    • +
    +

    Changes to enable custom tracks

    +
    • New S3 classes to store custom genomic features: CUSTOM_data and CUSTOM_data_thr.

    • +
    • create_hidecan_plot() now accepts CUSTOM_data_thr objects as input, which allows users to add custom tracks to their plot. It has an additional argument custom_aes to handle the aesthetics for custom tracks.

    • +
    • Added the hidecan_aes() function which returns the default aesthetics for the different types of data in the plot.

    +

    hidecan 1.1.0

    CRAN release: 2023-02-10

    • Removed get_gwaspoly_example_data() function so that the package doesn’t depend on GWASpoly (for CRAN submission)

    • @@ -57,7 +64,7 @@

      hidecan 1.1.0

    diff --git a/pkgdown.js b/pkgdown.js index 9757bf9..1a99c65 100644 --- a/pkgdown.js +++ b/pkgdown.js @@ -152,3 +152,11 @@ async function searchFuse(query, callback) { }); }); })(window.jQuery || window.$) + +document.addEventListener('keydown', function(event) { + // Check if the pressed key is '/' + if (event.key === '/') { + event.preventDefault(); // Prevent any default action associated with the '/' key + document.getElementById('search-input').focus(); // Set focus to the search input + } +}); diff --git a/pkgdown.yml b/pkgdown.yml index e9d7b9e..e9963b1 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -1,12 +1,13 @@ pandoc: 3.1.11 -pkgdown: 2.1.0 +pkgdown: 2.1.1 pkgdown_sha: ~ articles: + web_only/custom_tracks: web_only/custom_tracks.html web_only/gwaspoly_output: web_only/gwaspoly_output.html hidecan-step-by-step: hidecan-step-by-step.html hidecan: hidecan.html web_only/shiny-app: web_only/shiny-app.html -last_built: 2024-08-04T23:51Z +last_built: 2024-09-18T05:23Z urls: reference: https://plantandfoodresearch.github.io/hidecan/reference article: https://plantandfoodresearch.github.io/hidecan/articles diff --git a/reference/CAN_data.html b/reference/CAN_data.html index 22e7592..2a91a6d 100644 --- a/reference/CAN_data.html +++ b/reference/CAN_data.html @@ -21,6 +21,7 @@ @@ -106,7 +107,7 @@

    Examples -

    Site built with pkgdown 2.1.0.

    +

    Site built with pkgdown 2.1.1.

    diff --git a/reference/CUSTOM_data.html b/reference/CUSTOM_data.html new file mode 100644 index 0000000..ea9d0fc --- /dev/null +++ b/reference/CUSTOM_data.html @@ -0,0 +1,118 @@ + +Creates a CUSTOM_data object — CUSTOM_data • hidecan + Skip to contents + + +
    +
    +
    + +
    +

    Creates a CUSTOM_data object from a tibble or data-frame of custom genomic features.

    +
    + +
    +

    Usage

    +
    CUSTOM_data(dat, keep_rownames_as = NULL)
    +
    + +
    +

    Arguments

    + + +
    dat
    +

    Tibble of custom genomic features. See Details.

    + + +
    keep_rownames_as
    +

    Character, the name of the column in which to save the +rownames of the input data-frame. Default value is NULL, i.e. rownames will +be discarded.

    + +
    +
    +

    Value

    +

    A CUSTOM_data object, i.e. a tibble.

    +
    +
    +

    Details

    +

    The input data should have one row per marker, and at least the +following columns:

    • chromosome: character column, chromosome on which the feature is located.

    • +
    • position: numeric, the physical position of the feature along the chromosome (in bp).

    • +
    • score: numeric, score to be used for the genomic feature.

    • +
    + +
    +

    Examples

    +
    x <- get_example_data()
    +
    +CUSTOM_data(x[["GWAS"]])
    +#> # A tibble: 35,481 × 4
    +#>    id                  chromosome position score
    +#>    <chr>               <chr>         <dbl> <dbl>
    +#>  1 ST4.03ch00_45467783 ST4.03ch00 45467783 0.191
    +#>  2 ST4.03ch01_88589716 ST4.03ch01 88589716 1.84 
    +#>  3 ST4.03ch02_48614228 ST4.03ch02 48614228 0.381
    +#>  4 ST4.03ch03_62263578 ST4.03ch03 62263578 0.661
    +#>  5 ST4.03ch04_72139135 ST4.03ch04 72139135 0.640
    +#>  6 ST4.03ch05_52040302 ST4.03ch05 52040302 0.346
    +#>  7 ST4.03ch06_59434834 ST4.03ch06 59434834 1.13 
    +#>  8 ST4.03ch07_56713057 ST4.03ch07 56713057 0.213
    +#>  9 ST4.03ch08_56937627 ST4.03ch08 56937627 0.843
    +#> 10 ST4.03ch09_61537423 ST4.03ch09 61537423 0.512
    +#> # ℹ 35,471 more rows
    +
    +
    +
    + + +
    + + + +
    + + + + + + + diff --git a/reference/DE_data.html b/reference/DE_data.html index 825e3ea..978ce72 100644 --- a/reference/DE_data.html +++ b/reference/DE_data.html @@ -23,6 +23,7 @@ @@ -114,7 +115,7 @@

    Examples -

    Site built with pkgdown 2.1.0.

    +

    Site built with pkgdown 2.1.1.

    diff --git a/reference/GWAS_data.html b/reference/GWAS_data.html index 256a128..78bbd03 100644 --- a/reference/GWAS_data.html +++ b/reference/GWAS_data.html @@ -21,6 +21,7 @@ @@ -105,7 +106,7 @@

    Examples -

    Site built with pkgdown 2.1.0.

    +

    Site built with pkgdown 2.1.1.

    diff --git a/reference/GWAS_data_from_gwaspoly.html b/reference/GWAS_data_from_gwaspoly.html index c2fcafb..f55f028 100644 --- a/reference/GWAS_data_from_gwaspoly.html +++ b/reference/GWAS_data_from_gwaspoly.html @@ -21,6 +21,7 @@ @@ -89,7 +90,7 @@

    Value

    diff --git a/reference/apply_threshold.CUSTOM_data.html b/reference/apply_threshold.CUSTOM_data.html new file mode 100644 index 0000000..ed8103b --- /dev/null +++ b/reference/apply_threshold.CUSTOM_data.html @@ -0,0 +1,8 @@ + + + + + + + + diff --git a/reference/apply_threshold.html b/reference/apply_threshold.html index e73a3f6..3314981 100644 --- a/reference/apply_threshold.html +++ b/reference/apply_threshold.html @@ -27,6 +27,7 @@ @@ -65,6 +66,9 @@

    Examples -

    Site built with pkgdown 2.1.0.

    +

    Site built with pkgdown 2.1.1.

    diff --git a/reference/new_CAN_data.html b/reference/new_CAN_data.html index 3f25ef1..e7bdd27 100644 --- a/reference/new_CAN_data.html +++ b/reference/new_CAN_data.html @@ -21,6 +21,7 @@ @@ -71,7 +72,7 @@

    Value

    diff --git a/reference/new_CUSTOM_data.html b/reference/new_CUSTOM_data.html new file mode 100644 index 0000000..7f255cd --- /dev/null +++ b/reference/new_CUSTOM_data.html @@ -0,0 +1,85 @@ + +CUSTOM_data constructor — new_CUSTOM_data • hidecan + Skip to contents + + +
    +
    +
    + +
    +

    CUSTOM_data constructor

    +
    + +
    +

    Usage

    +
    new_CUSTOM_data(dat)
    +
    + +
    +

    Arguments

    + + +
    dat
    +

    Tibble, custom genomic features, with at least columns +chromosome, position and score.

    + +
    +
    +

    Value

    +

    A GWAS_data object, i.e. a tibble.

    +
    + +
    + + +
    + + + +
    + + + + + + + diff --git a/reference/new_DE_data.html b/reference/new_DE_data.html index 4ae5974..9c9dcc9 100644 --- a/reference/new_DE_data.html +++ b/reference/new_DE_data.html @@ -21,6 +21,7 @@ @@ -71,7 +72,7 @@

    Value

    diff --git a/reference/new_GWAS_data.html b/reference/new_GWAS_data.html index 29baf68..e8537a1 100644 --- a/reference/new_GWAS_data.html +++ b/reference/new_GWAS_data.html @@ -21,6 +21,7 @@ @@ -71,7 +72,7 @@

    Value

    diff --git a/reference/run_hidecan_shiny.html b/reference/run_hidecan_shiny.html index c57a84e..21e107c 100644 --- a/reference/run_hidecan_shiny.html +++ b/reference/run_hidecan_shiny.html @@ -23,6 +23,7 @@ @@ -65,7 +66,7 @@

    Value

    diff --git a/reference/validate_CAN_data.html b/reference/validate_CAN_data.html index dc51dcc..6506c35 100644 --- a/reference/validate_CAN_data.html +++ b/reference/validate_CAN_data.html @@ -21,6 +21,7 @@ @@ -70,7 +71,7 @@

    Value

    diff --git a/reference/validate_CUSTOM_data.html b/reference/validate_CUSTOM_data.html new file mode 100644 index 0000000..d0a7072 --- /dev/null +++ b/reference/validate_CUSTOM_data.html @@ -0,0 +1,84 @@ + +Checks validity of input for CUSTOM_data constructor — validate_CUSTOM_data • hidecan + Skip to contents + + +
    +
    +
    + +
    +

    Checks validity of input for CUSTOM_data constructor

    +
    + +
    +

    Usage

    +
    validate_CUSTOM_data(x)
    +
    + +
    +

    Arguments

    + + +
    x,
    +

    a CUSTOM_data object constructed via new_CUSTOM_data.

    + +
    +
    +

    Value

    +

    A CUSTOM_data object, i.e. a tibble.

    +
    + +
    + + +
    + + + +
    + + + + + + + diff --git a/reference/validate_DE_data.html b/reference/validate_DE_data.html index 3e716ae..5979bc7 100644 --- a/reference/validate_DE_data.html +++ b/reference/validate_DE_data.html @@ -21,6 +21,7 @@ @@ -70,7 +71,7 @@

    Value

    diff --git a/reference/validate_GWAS_data.html b/reference/validate_GWAS_data.html index 1a46053..e2c50c1 100644 --- a/reference/validate_GWAS_data.html +++ b/reference/validate_GWAS_data.html @@ -21,6 +21,7 @@ @@ -70,7 +71,7 @@

    Value

    diff --git a/search.json b/search.json index 78f603e..94f6f55 100644 --- a/search.json +++ b/search.json @@ -1 +1 @@ -[{"path":"https://plantandfoodresearch.github.io/hidecan/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2023 hidecan authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan-step-by-step.html","id":"formatting-input-data","dir":"Articles","previous_headings":"","what":"Formatting input data","title":"Creating a HIDECAN plot step by step","text":"hood, hidecan package relies S3 classes, really just tibbles specific columns. constructors S3 classes perform series checks computations make sure required columns (chromosome, score, position) present data. GWAS results data-frames turned GWAS_data objects GWAS_data() constructor: DE results data-frames turned DE_data objects DE_data() constructor: Candidate genes data-frames turned CAN_data objects CAN_data() constructor: constructors throw error required column missing input data (e.g. chromosome column): also compute marker gene scores adjusted p-values necessary (see Input data section hidecan vignette). example, DE results, provide padj column (adjusted p-values genes) rather score column, constructor compute score column based padj column. can also notice position column computed based start end genes:","code":"gwas_data <- GWAS_data(x[[\"GWAS\"]]) class(gwas_data) #> [1] \"GWAS_data\" \"tbl_df\" \"tbl\" \"data.frame\" head(gwas_data) #> # A tibble: 6 × 4 #> id chromosome position score #> #> 1 ST4.03ch00_45467783 ST4.03ch00 45467783 0.191 #> 2 ST4.03ch01_88589716 ST4.03ch01 88589716 1.84 #> 3 ST4.03ch02_48614228 ST4.03ch02 48614228 0.381 #> 4 ST4.03ch03_62263578 ST4.03ch03 62263578 0.661 #> 5 ST4.03ch04_72139135 ST4.03ch04 72139135 0.640 #> 6 ST4.03ch05_52040302 ST4.03ch05 52040302 0.346 de_data <- DE_data(x[[\"DE\"]]) class(de_data) #> [1] \"DE_data\" \"tbl_df\" \"tbl\" \"data.frame\" head(de_data) #> # A tibble: 6 × 9 #> gene chromosome padj log2FoldChange start end label score position #> #> 1 PGSC000… ST4.03ch00 0.787 0.0114 4.58e7 4.58e7 Prot… 0.104 4.58e7 #> 2 PGSC000… ST4.03ch01 0.630 0.00529 8.86e7 8.86e7 PhD-… 0.201 8.86e7 #> 3 PGSC000… ST4.03ch02 0.864 0.00362 4.86e7 4.86e7 Acet… 0.0637 4.86e7 #> 4 PGSC000… ST4.03ch03 0.530 0.0320 6.23e7 6.23e7 Phos… 0.276 6.23e7 #> 5 PGSC000… ST4.03ch04 0.975 0.00225 7.22e7 7.22e7 Cons… 0.0109 7.22e7 #> 6 PGSC000… ST4.03ch05 NA -0.000726 5.20e7 5.20e7 Cons… NA 5.20e7 ## CAN_data constructor can_data <- CAN_data(x[[\"CAN\"]]) class(can_data) #> [1] \"CAN_data\" \"tbl_df\" \"tbl\" \"data.frame\" head(can_data) #> # A tibble: 6 × 7 #> id chromosome start end name gene_name position #> #> 1 PGSC0003DMG400003155 ST4.03ch03 46757152 46762127 4CL 4-coumar… 4.68e7 #> 2 PGSC0003DMG400014223 ST4.03ch03 57466692 57469946 4CL2 4-coumar… 5.75e7 #> 3 PGSC0003DMG400011189 ST4.03ch07 1001854 1006278 HQT HQT 1.00e6 #> 4 PGSC0003DMG400005492 ST4.03ch05 36342746 36347409 PAL phenylal… 3.63e7 #> 5 PGSC0003DMG400005279 ST4.03ch05 42523943 42525912 peroxida… peroxida… 4.25e7 #> 6 PGSC0003DMG400007782 ST4.03ch03 38537202 38540209 PHO1A PHO1A 3.85e7 gwas_wrong_input <- x[[\"GWAS\"]] |> select(-chromosome) GWAS_data(gwas_wrong_input) #> Error: Input data-frame is missing the following columns: 'chromosome'. ## Input tibble head(x[[\"DE\"]]) #> # A tibble: 6 × 7 #> gene chromosome padj log2FoldChange start end label #> #> 1 PGSC0003DMG400032056 ST4.03ch00 0.787 0.0114 45813195 45813526 Prote… #> 2 PGSC0003DMG400018039 ST4.03ch01 0.630 0.00529 88623473 88627702 PhD-f… #> 3 PGSC0003DMG400020231 ST4.03ch02 0.864 0.00362 48563271 48578978 Acety… #> 4 PGSC0003DMG400009197 ST4.03ch03 0.530 0.0320 62256322 62258929 Phosp… #> 5 PGSC0003DMG403025662 ST4.03ch04 0.975 0.00225 72168842 72170119 Conse… #> 6 PGSC0003DMG400023316 ST4.03ch05 NA -0.000726 52039916 52040326 Conse… ## Output of the DE_data constructor head(de_data) #> # A tibble: 6 × 9 #> gene chromosome padj log2FoldChange start end label score position #> #> 1 PGSC000… ST4.03ch00 0.787 0.0114 4.58e7 4.58e7 Prot… 0.104 4.58e7 #> 2 PGSC000… ST4.03ch01 0.630 0.00529 8.86e7 8.86e7 PhD-… 0.201 8.86e7 #> 3 PGSC000… ST4.03ch02 0.864 0.00362 4.86e7 4.86e7 Acet… 0.0637 4.86e7 #> 4 PGSC000… ST4.03ch03 0.530 0.0320 6.23e7 6.23e7 Phos… 0.276 6.23e7 #> 5 PGSC000… ST4.03ch04 0.975 0.00225 7.22e7 7.22e7 Cons… 0.0109 7.22e7 #> 6 PGSC000… ST4.03ch05 NA -0.000726 5.20e7 5.20e7 Cons… NA 5.20e7"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan-step-by-step.html","id":"computing-chromosome-length","dir":"Articles","previous_headings":"","what":"Computing chromosome length","title":"Creating a HIDECAN plot step by step","text":"input datasets formatted appropriately, used compute length chromosomes present data. done combine_chrom_length() function, applied list GWAS_data, DE_data CAN_data objects: function works calling element list compute_chrom_length() function. function, according whether input tibble markers (GWAS_data) genes (DE_data CAN_data), looks maximum value either position column (markers) end column (genes).","code":"chrom_length <- combine_chrom_length(list(gwas_data, de_data, can_data)) chrom_length #> # A tibble: 13 × 2 #> chromosome length #> #> 1 ST4.03ch00 45813526 #> 2 ST4.03ch01 88627702 #> 3 ST4.03ch02 48614228 #> 4 ST4.03ch03 62263578 #> 5 ST4.03ch04 72170119 #> 6 ST4.03ch05 52040326 #> 7 ST4.03ch06 59476545 #> 8 ST4.03ch07 56715111 #> 9 ST4.03ch08 56937627 #> 10 ST4.03ch09 61539681 #> 11 ST4.03ch10 59687482 #> 12 ST4.03ch11 45409456 #> 13 ST4.03ch12 61152223 head(compute_chrom_length(gwas_data), 3) #> # A tibble: 3 × 2 #> chromosome length #> #> 1 ST4.03ch00 45467783 #> 2 ST4.03ch01 88589716 #> 3 ST4.03ch02 48614228 head(compute_chrom_length(de_data), 3) #> # A tibble: 3 × 2 #> chromosome length #> #> 1 ST4.03ch00 45813526 #> 2 ST4.03ch01 88627702 #> 3 ST4.03ch02 48578978"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan-step-by-step.html","id":"applying-threshold","dir":"Articles","previous_headings":"","what":"Applying threshold","title":"Creating a HIDECAN plot step by step","text":"Next, GWAS DE results tibbles filtered according threshold, order retain significant markers genes. done apply_threshold() function. function two (rather self-explanatory) arguments: score_thr log2fc_thr. applied GWAS_data object, function filters markers score value set score_thr argument (log2fc_thr argument ignored), returns object class GWAS_data_thr: DE_data object, apply_threshold function filters genes based score log2(fold-change), returns object class DE_data_thr: Finally, applied CAN_data object, apply_threshold() function simply returns input tibble object class CAN_data_thr: GWAS_data, DE_data CAN_data objects, GWAS_data_thr, DE_data_thr CAN_data_thr objects really just tibbles.","code":"dim(gwas_data) #> [1] 35481 4 gwas_data_thr <- apply_threshold(gwas_data, score_thr = 4) class(gwas_data_thr) #> [1] \"GWAS_data_thr\" \"tbl_df\" \"tbl\" \"data.frame\" dim(gwas_data_thr) #> [1] 37 4 head(gwas_data_thr) #> # A tibble: 6 × 4 #> id chromosome position score #> #> 1 ST4.03ch00_22680252 ST4.03ch00 22680252 4.41 #> 2 ST4.03ch01_6317643 ST4.03ch01 6317643 4.15 #> 3 ST4.03ch01_7671100 ST4.03ch01 7671100 4.43 #> 4 ST4.03ch01_8653747 ST4.03ch01 8653747 4.69 #> 5 ST4.03ch01_12842648 ST4.03ch01 12842648 6.85 #> 6 ST4.03ch01_13334335 ST4.03ch01 13334335 5.24 dim(de_data) #> [1] 10671 9 de_data_thr <- apply_threshold(de_data, score_thr = 2, log2fc_thr = 0.5) class(de_data_thr) #> [1] \"DE_data_thr\" \"tbl_df\" \"tbl\" \"data.frame\" dim(de_data_thr) #> [1] 2 9 head(de_data_thr) #> # A tibble: 2 × 9 #> gene chromosome padj log2FoldChange start end label score position #> #> 1 PGSC0003… ST4.03ch10 0.00480 0.757 3.30e7 3.30e7 Cons… 2.32 3.30e7 #> 2 PGSC0003… ST4.03ch10 0.00305 0.691 5.82e7 5.82e7 N-ac… 2.52 5.82e7 dim(can_data) #> [1] 32 7 can_data_thr <- apply_threshold(can_data, score_thr = 2, log2fc_thr = 0.5) class(can_data_thr) #> [1] \"CAN_data_thr\" \"tbl_df\" \"tbl\" \"data.frame\" dim(can_data_thr) #> [1] 32 7 head(can_data_thr) #> # A tibble: 6 × 7 #> id chromosome start end name gene_name position #> #> 1 PGSC0003DMG400003155 ST4.03ch03 46757152 46762127 4CL 4-coumar… 4.68e7 #> 2 PGSC0003DMG400014223 ST4.03ch03 57466692 57469946 4CL2 4-coumar… 5.75e7 #> 3 PGSC0003DMG400011189 ST4.03ch07 1001854 1006278 HQT HQT 1.00e6 #> 4 PGSC0003DMG400005492 ST4.03ch05 36342746 36347409 PAL phenylal… 3.63e7 #> 5 PGSC0003DMG400005279 ST4.03ch05 42523943 42525912 peroxida… peroxida… 4.25e7 #> 6 PGSC0003DMG400007782 ST4.03ch03 38537202 38540209 PHO1A PHO1A 3.85e7"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan-step-by-step.html","id":"creating-the-hidecan-plot","dir":"Articles","previous_headings":"","what":"Creating the HIDECAN plot","title":"Creating a HIDECAN plot step by step","text":"Finally, filtered datasets combined list passed create_hidecan_plot() function, along tibble chromosome length. function generates HIDECAN ggplot: function shares arguments hidecan_plot() wrapper controlling different aspects plot.","code":"create_hidecan_plot( list(gwas_data_thr, de_data_thr, can_data_thr), chrom_length )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"input-data","dir":"Articles","previous_headings":"","what":"Input data","title":"hidecan","text":"hidecan package takes input tibbles (data-frames) GWAS DE results candidate genes. input data-frames contain mandatory columns, depending type data. list example input datasets can obtained via get_example_data() function:","code":"x <- get_example_data() str(x, max.level = 1) #> List of 3 #> $ GWAS: tibble [35,481 × 4] (S3: tbl_df/tbl/data.frame) #> $ DE : tibble [10,671 × 7] (S3: tbl_df/tbl/data.frame) #> $ CAN : tibble [32 × 6] (S3: tbl_df/tbl/data.frame)"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"gwas-results","dir":"Articles","previous_headings":"Input data","what":"GWAS results","title":"hidecan","text":"GWAS results provided tibble data-frame, one row per genetic marker. data-frame contain least following columns: chromosome: character column, giving ID chromosome marker located; position: numeric column, physical position along chromosome (base pairs - bp) marker; either score padj: numeric column, providing either score (.e. -log10(p-value)) adjusted p-value marker. score column provided, padj column ignored. padj column provided, score column constructed -log10(padj). column present data-frame ignored. example valid input shown :","code":"head(x[[\"GWAS\"]]) #> # A tibble: 6 × 4 #> id chromosome position score #> #> 1 ST4.03ch00_45467783 ST4.03ch00 45467783 0.191 #> 2 ST4.03ch01_88589716 ST4.03ch01 88589716 1.84 #> 3 ST4.03ch02_48614228 ST4.03ch02 48614228 0.381 #> 4 ST4.03ch03_62263578 ST4.03ch03 62263578 0.661 #> 5 ST4.03ch04_72139135 ST4.03ch04 72139135 0.640 #> 6 ST4.03ch05_52040302 ST4.03ch05 52040302 0.346"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"differential-expression-results","dir":"Articles","previous_headings":"Input data","what":"Differential expression results","title":"hidecan","text":"DE results provided tibble data-frame, one row per gene. data-frame contain least following columns: chromosome: character column, giving ID chromosome gene located; start end: numeric columns, giving starting end position gene along chromosome (bp). two columns used calculate position gene half-way point start end gene. either score padj: numeric column, providing either score (.e. -log10(p-value)) adjusted p-value gene. score column provided, padj column ignored. padj column provided, score column constructed -log10(padj). either foldChange log2FoldChange: numeric column, giving either fold-change log2(fold-change) gene. log2FoldChange column provided, foldChange column ignored. foldChange column provided, log2FoldChange constructed log2(foldChange). column present data-frame ignored. example valid input shown : (Note example dataset, genes missing values padj column; corresponds genes filtered via independent filtering DESeq2 package).","code":"head(x[[\"DE\"]]) #> # A tibble: 6 × 7 #> gene chromosome padj log2FoldChange start end label #> #> 1 PGSC0003DMG400032056 ST4.03ch00 0.787 0.0114 45813195 45813526 Prote… #> 2 PGSC0003DMG400018039 ST4.03ch01 0.630 0.00529 88623473 88627702 PhD-f… #> 3 PGSC0003DMG400020231 ST4.03ch02 0.864 0.00362 48563271 48578978 Acety… #> 4 PGSC0003DMG400009197 ST4.03ch03 0.530 0.0320 62256322 62258929 Phosp… #> 5 PGSC0003DMG403025662 ST4.03ch04 0.975 0.00225 72168842 72170119 Conse… #> 6 PGSC0003DMG400023316 ST4.03ch05 NA -0.000726 52039916 52040326 Conse…"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"candidate-genes","dir":"Articles","previous_headings":"Input data","what":"Candidate genes","title":"hidecan","text":"list candidate genes (e.g. genes previously found associated trait interest based literature search) can provided tibble data-frame, one row per gene. data-frame can also contain variants interest (see ). data-frame contain least following columns: chromosome: character column, giving ID chromosome gene located; start end: numeric columns, giving starting end position gene along chromosome (bp). two columns used calculate position gene half-way point start end gene. genomic variants markers, simply set start end columns physical position marker. name: character column, giving name candidate gene displayed HIDECAN plot. Set NA subset genes remove label plot (can help many genes close, avoid cluttering plot). column present data-frame ignored. example valid input shown :","code":"head(x[[\"CAN\"]]) #> # A tibble: 6 × 6 #> id chromosome start end name gene_name #> #> 1 PGSC0003DMG400003155 ST4.03ch03 46757152 46762127 4CL 4-coumarate-CoA … #> 2 PGSC0003DMG400014223 ST4.03ch03 57466692 57469946 4CL2 4-coumarate-CoA … #> 3 PGSC0003DMG400011189 ST4.03ch07 1001854 1006278 HQT HQT #> 4 PGSC0003DMG400005492 ST4.03ch05 36342746 36347409 PAL phenylalanine am… #> 5 PGSC0003DMG400005279 ST4.03ch05 42523943 42525912 peroxidase peroxidase #> 6 PGSC0003DMG400007782 ST4.03ch03 38537202 38540209 PHO1A PHO1A"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"creating-a-hidecan-plot","dir":"Articles","previous_headings":"","what":"Creating a HIDECAN plot","title":"hidecan","text":"hidecan_plot() function creates HIDECAN plot. takes input data-frames presented , well score log2(fold-change) thresholds used select significant markers genes. example, show markers score 4, corresponds p-value 1×10−41\\times10^{-4}, genes score 1.3, corresponds p-value 0.05. don’t place threshold log2(fold-change) genes: Note possible provide subset possible input data, e.g. GWAS results list candidate genes:","code":"hidecan_plot( gwas_list = x[[\"GWAS\"]], ## data-frame of GWAS results de_list = x[[\"DE\"]], ## data-frame of DE results can_list = x[[\"CAN\"]], ## data-frame of candidate genes score_thr_gwas = -log10(0.0001), ## sign. threshold for GWAS score_thr_de = -log10(0.05), ## sign. threshold for DE log2fc_thr = 0 ## log2FC threshold for DE ) hidecan_plot( gwas_list = x[[\"GWAS\"]], can_list = x[[\"CAN\"]], score_thr_gwas = 4 )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"removing-empty-chromosomes","dir":"Articles","previous_headings":"","what":"Removing empty chromosomes","title":"hidecan","text":"default, HIDECAN plot shows chromosomes present input data. However, possible chromosomes appear empty, contain significant gene marker, candidate gene. case, possible exclude “empty” chromosomes HIDECAN plot, remove_empty_chrom argument. demonstrate increasing score threshold applied GWAS results, order get fewer significant markers. case, chromosomes 0, 6, 9 10 contain significant marker gene interest: setting remove_empty_chrom argument TRUE, chromosomes removed plot:","code":"## Chromosomes 0, 6, 9 and 10 are empty hidecan_plot( gwas_list = x[[\"GWAS\"]], can_list = x[[\"CAN\"]], score_thr_gwas = 5 ) hidecan_plot( gwas_list = x[[\"GWAS\"]], can_list = x[[\"CAN\"]], score_thr_gwas = 5, remove_empty_chrom = TRUE )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"selecting-chromosomes-and-genomic-positions","dir":"Articles","previous_headings":"","what":"Selecting chromosomes and genomic positions","title":"hidecan","text":"possible specify chromosomes represented HIDECAN plot, via chroms argument. example, following command restrict plot chromosomes 7 8: can also “zoom ” chromosomes, chrom_limits argument. zoom chromosomes , pass chrom_limits argument integer vector length 2, gives lower upper limits bp use. example , focus 10-20Mb region chromosome: Alternatively, can apply different limits chromosomes, passing named list argument. names list match chromosomes name, element integer vector length 2 giving lower upper limits bp use corresponding chromosome. example, focus 10-20Mb region chromosome 1, 30-40Mb region chromosome 5, leave chromosomes : two options chroms chrom_limits can used together:","code":"hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, chroms = c(\"ST4.03ch07\", \"ST4.03ch08\") ) hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, chrom_limits = c(10e6, 20e6) ) hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, chrom_limits = list(\"ST4.03ch01\" = c(10e6, 20e6), \"ST4.03ch05\" = c(30e6, 40e6)) ) hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, chroms = c(\"ST4.03ch07\", \"ST4.03ch08\"), chrom_limits = list(\"ST4.03ch07\" = c(50e6, 55e6), \"ST4.03ch08\" = c(45e6, 50e6)) )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"colour-genes-by-log2fold-change","dir":"Articles","previous_headings":"","what":"Colour genes by log2(fold-change)","title":"hidecan","text":"default, HIDECAN plot, points representing significant markers DE genes coloured according GWAS/DE score. However, possible colour DE genes log2(fold-change) value instead, setting colour_genes_by_score argument FALSE: Genes negative log2(fold-change) represented shade blue, genes positive log2(fold-change) represented shade red.","code":"hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, colour_genes_by_score = FALSE )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"more-than-one-gwas-de-or-candidate-gene-list","dir":"Articles","previous_headings":"","what":"More than one GWAS, DE or candidate gene list","title":"hidecan","text":"hidecan_plot() function can take input lists data-frames GWAS results, DE results candidate genes. way, possible visualise one GWAS DE analyses , example investigating several traits comparing two treatment groups. example, ’ll focus chromosomes 7 8 (clarity plot): ’ll create second data-frame GWAS results shuffling marker scores example dataset: can pass GWAS results data-frames hidecan_plot() function list: default, two GWAS tracks given unique y-axis labels, can seen . possible customise naming elements input list:","code":"library(dplyr) library(purrr) library(stringr) ## Retaining only markers and genes on chromosomes 7 and 8 x_small <- x |> map(~ filter(.x, str_detect(chromosome, \"(07|08)\"))) ## Creating a second GWAS result tibble by shuffling ## the marker scores from the original data gwas_1 <- x_small[[\"GWAS\"]] gwas_2 <- gwas_1 |> mutate(score = sample(score)) hidecan_plot( gwas_list = list(gwas_1, gwas_2), score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0 ) hidecan_plot( gwas_list = list(\"Trait 1\" = gwas_1, \"Trait 2\" = gwas_2), score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0 )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"defining-chromosomes-length","dir":"Articles","previous_headings":"","what":"Defining chromosomes length","title":"hidecan","text":"default, hidecan_plot() function calculates length different chromosomes based input data, looking maximum position genes markers chromosome. However, also possible pass tibble chromosome length (bp) chrom_length argument. Note case can’t really see difference computed chromosome length values.","code":"library(tibble) ## Chromosomes length as recorded in Ensembl Plants potato_chrom_length <- c( ST4.03ch00 = 45813526, ST4.03ch01 = 88663952, ST4.03ch02 = 48614681, ST4.03ch03 = 62190286, ST4.03ch04 = 72208621, ST4.03ch05 = 52070158, ST4.03ch06 = 59532096, ST4.03ch07 = 56760843, ST4.03ch08 = 56938457, ST4.03ch09 = 61540751, ST4.03ch10 = 59756223, ST4.03ch11 = 45475667, ST4.03ch12 = 61165649 ) |> ## turn a named vector into a tibble enframe(name = \"chromosome\", value = \"length\") head(potato_chrom_length) #> # A tibble: 6 × 2 #> chromosome length #> #> 1 ST4.03ch00 45813526 #> 2 ST4.03ch01 88663952 #> 3 ST4.03ch02 48614681 #> 4 ST4.03ch03 62190286 #> 5 ST4.03ch04 72208621 #> 6 ST4.03ch05 52070158 hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, chrom_length = potato_chrom_length )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"controlling-the-plot-properties","dir":"Articles","previous_headings":"","what":"Controlling the plot properties","title":"hidecan","text":"hidecan_plot() function offers several arguments control different aspects HIDECAN plot. example, possible specify number rows columns plot , n_rows n_cols arguments. Note one arguments considered (n_rows takes precedence): addition, possible : add title subtitle plot (title subtitle arguments); control position legend (legend_position argument); control size points (point_size argument); control size labels padding around text candidate genes labels (label_size label_padding arguments).","code":"## Specifying the number of rows hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, n_rows = 3 ) ## Specifying the number of columns hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.005), log2fc_thr = 0, n_cols = 3 )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"creating-a-manhattan-plot","dir":"Articles","previous_headings":"","what":"Creating a Manhattan plot","title":"hidecan","text":"possible visualise GWAS results Manhattan plot manhattan_plot() function. function takes input data-frame (list data-frames) GWAS results, must follow rules plot_hidecan() function (see section vignette). horizontal line representing significance threshold can added plot, passing threshold value score_thr argument. hidecan_plot() function, possible pass list GWAS results function, order draw several Manhattan plots one figure. names list used identify different plots:","code":"manhattan_plot(x[[\"GWAS\"]], score_thr = 4) manhattan_plot(list(\"Trait A\" = x[[\"GWAS\"]], \"Trait B\" = x[[\"GWAS\"]]), score_thr = 4, ncol = 1)"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"viewport-error","dir":"Articles","previous_headings":"","what":"Viewport error","title":"hidecan","text":"working RStudio, may encounter following error: caused plotting window small. Try increasing size plotting window RStudio console. Alternatively, can save plot R object, use ggplot2::ggsave() save file:","code":"#> Error in grid.Call(C_convert, x, as.integer(whatfrom), as.integer(whatto), : Viewport has zero dimension(s) p <- hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, label_size = 2 ) ggplot2::ggsave(\"hidecan_plot.pdf\", p, width = 10, height = 10)"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/web_only/gwaspoly_output.html","id":"gwaspoly-example-data","dir":"Articles > Web_only","previous_headings":"","what":"GWASpoly example data","title":"HIDECAN plot from GWASpoly output","text":"example GWASpoly output, based original example dataset GWASpoly package provided package can loaded 1: example, three traits analysed: tuber_eye_depth, tuber_shape sucrose. trait, GWAS scores computed four different genetic models: general, additive, 1-dom-alt 1-dom-ref: See Appendix section bottom vignette code used generate example data.","code":"gwaspoly_res_thr <- readRDS(system.file(\"extdata/gwaspoly_res_thr.rda\", package = \"hidecan\")) ## Traits analysed names(gwaspoly_res_thr@scores) #> [1] \"tuber_eye_depth\" \"tuber_shape\" \"sucrose\" ## Genetic models tests head(gwaspoly_res_thr@scores[[1]]) #> general additive 1-dom-alt 1-dom-ref #> c2_41437 0.45584445 0.4774282 0.1430731 NA #> c2_24258 0.32552500 0.1655215 NA 0.0431065 #> c2_21332 0.06251865 0.2263273 0.1562208 0.4488712 #> c2_21320 0.92927679 0.5774697 NA 1.0170807 #> c2_21318 0.09043940 0.2200563 0.1410284 NA #> c2_21314 0.19480464 0.6442068 NA 0.4286548"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/web_only/gwaspoly_output.html","id":"hidecan-plot-from-gwaspoly-output","dir":"Articles > Web_only","previous_headings":"","what":"HIDECAN plot from GWASpoly output","title":"HIDECAN plot from GWASpoly output","text":"hidecan_plot_from_gwaspoly() function reads GWASpoly.thresh object, extracts marker scores combination trait genetic model, uses construct HIDECAN plot. y-axis, trait indicated first, genetic model next brackets: HIDECAN plot, can easily see genomic region around 50Mb chromosome 10 significantly associated tuber eye depth shape, using either general additive model. region significantly associated either traits considering one simplex dominant models. sucrose phenotype, general model detected significant markers. possible specify traits /genetic models represented HIDECAN plot, via traits models arguments:","code":"hidecan_plot_from_gwaspoly( gwaspoly_res_thr, remove_empty_chrom = TRUE ) hidecan_plot_from_gwaspoly( gwaspoly_res_thr, traits = c(\"tuber_eye_depth\", \"tuber_shape\"), models = \"general\", remove_empty_chrom = TRUE )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/web_only/gwaspoly_output.html","id":"the-gwaspoly-constructor","dir":"Articles > Web_only","previous_headings":"","what":"The GWASpoly constructor","title":"HIDECAN plot from GWASpoly output","text":"hood, hidecan_plot_from_gwaspoly() function relies GWAS_data_from_gwaspoly() constructor, takes input either: GWASpoly.fitted object (returned GWASpoly::GWASpoly() function), GWASpoly.thresh object (returned GWASpoly::set.threshold() function). function extracts marker scores traits genetic models present GWASpoly output, well length chromosomes. addition, input data GWASpoly.thresh object, extracts significance threshold combination trait genetic model, uses filter significant markers.","code":"gwaspoly_data <- GWAS_data_from_gwaspoly(gwaspoly_res_thr) ## GWAS_data objects, i.e. tibbles of marker scores str(gwaspoly_data$gwas_data_list, max.level = 1) #> List of 12 #> $ tuber_eye_depth (general) : GWAS_dat [3,507 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ tuber_eye_depth (additive) : GWAS_dat [3,507 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ tuber_eye_depth (1-dom-alt): GWAS_dat [2,054 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ tuber_eye_depth (1-dom-ref): GWAS_dat [2,174 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ tuber_shape (general) : GWAS_dat [3,507 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ tuber_shape (additive) : GWAS_dat [3,507 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ tuber_shape (1-dom-alt) : GWAS_dat [2,054 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ tuber_shape (1-dom-ref) : GWAS_dat [2,174 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ sucrose (general) : GWAS_dat [3,506 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ sucrose (additive) : GWAS_dat [3,507 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ sucrose (1-dom-alt) : GWAS_dat [2,054 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ sucrose (1-dom-ref) : GWAS_dat [2,174 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) ## GWAS_data_thr objects, i.e. tibbles of significant markers str(gwaspoly_data$gwas_data_thr_list, max.level = 1) #> List of 12 #> $ tuber_eye_depth (general) : GWAS_dt_ [1 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ tuber_eye_depth (additive) : GWAS_dt_ [3 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ tuber_eye_depth (1-dom-alt): GWAS_dt_ [0 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ tuber_eye_depth (1-dom-ref): GWAS_dt_ [0 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ tuber_shape (general) : GWAS_dt_ [2 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ tuber_shape (additive) : GWAS_dt_ [2 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ tuber_shape (1-dom-alt) : GWAS_dt_ [0 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ tuber_shape (1-dom-ref) : GWAS_dt_ [0 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ sucrose (general) : GWAS_dt_ [2 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ sucrose (additive) : GWAS_dt_ [0 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ sucrose (1-dom-alt) : GWAS_dt_ [0 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ sucrose (1-dom-ref) : GWAS_dt_ [0 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) ## Chromosomes length str(gwaspoly_data$chrom_length) #> tibble [13 × 2] (S3: tbl_df/tbl/data.frame) #> $ chromosome: Ord.factor w/ 13 levels \"0\"<\"1\"<\"2\"<\"3\"<..: 1 2 3 4 5 6 7 8 9 10 ... #> $ length : int [1:13] 36454137 88583876 48564909 61870684 72026885 51998374 59263222 56628128 56785385 61466245 ..."},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/web_only/gwaspoly_output.html","id":"appendix-reproducing-the-gwaspoly-example-data","dir":"Articles > Web_only","previous_headings":"","what":"Appendix: reproducing the GWASpoly example data","title":"HIDECAN plot from GWASpoly output","text":"example dataset provided can reproduced following code:","code":"library(GWASpoly) genofile <- system.file(\"extdata\", \"TableS1.csv\", package = \"GWASpoly\") phenofile <- system.file(\"extdata\", \"TableS2.csv\", package = \"GWASpoly\") ## Reading example data data <- read.GWASpoly( ploidy = 4, pheno.file = phenofile, geno.file = genofile, format = \"ACGT\", n.traits = 13, delim = \",\" ) ## Computing K matrix data.original <- set.K( data, LOCO = FALSE, n.core = 2 ) ## Performing GWAS gwaspoly_res <- GWASpoly( data.original, models = c(\"general\", \"additive\", \"1-dom\"), traits = c(\"tuber_eye_depth\", \"tuber_shape\", \"sucrose\"), n.core = 2 ) ## Computing significance threshold ## Object returned by get_gwaspoly_example_data() gwaspoly_res_thr <- set.threshold( gwaspoly_res, method = \"M.eff\", level = 0.05 ) # saveRDS(gwaspoly_res_thr, \"gwaspoly_res_thr.rda)"},{"path":"https://plantandfoodresearch.github.io/hidecan/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Olivia Angelin-Bonnet. Author, maintainer.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Angelin-Bonnet O (2024). hidecan: Create HIDECAN Plots Visualising Genome-Wide Association Studies Differential Expression Results. R package version 1.1.0.9000, https://github.com/PlantandFoodResearch/hidecan, https://plantandfoodresearch.github.io/hidecan/.","code":"@Manual{, title = {hidecan: Create HIDECAN Plots for Visualising Genome-Wide Association Studies and Differential Expression Results}, author = {Olivia Angelin-Bonnet}, year = {2024}, note = {R package version 1.1.0.9000, https://github.com/PlantandFoodResearch/hidecan}, url = {https://plantandfoodresearch.github.io/hidecan/}, }"},{"path":"https://plantandfoodresearch.github.io/hidecan/index.html","id":"hidecan-","dir":"","previous_headings":"","what":"Create HIDECAN Plots for Visualising Genome-Wide Association Studies and Differential Expression Results","title":"Create HIDECAN Plots for Visualising Genome-Wide Association Studies and Differential Expression Results","text":"hidecan R package generating HIDECAN plots, visualisations summarising results one Genome-wide association study (GWAS) transcriptomics differential expression (DE) analysis, alongside candidate genes interest.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Create HIDECAN Plots for Visualising Genome-Wide Association Studies and Differential Expression Results","text":"hidecan available CRAN can installed via: Alternatively, can install development version hidecan GitHub :","code":"install.packages(\"hidecan\") # install.packages(\"devtools\") devtools::install_github(\"PlantandFoodResearch/hidecan\")"},{"path":"https://plantandfoodresearch.github.io/hidecan/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"Create HIDECAN Plots for Visualising Genome-Wide Association Studies and Differential Expression Results","text":"hidecan package works follows: takes input one data-frames containing GWAS results, differential expression results list candidate genes interest; computes length chromosome based genomic position markers genes provided input data; filters datasets retain significant markers differentially expressed genes, according threshold score /log2-fold change. fold-change set user, can different GWAS differential expression results. displays position significant markers genes alongside candidate genes (HIDECAN plot). plot can customised user via number parameters (e.g. legend position label size). wrapper function hidecan_plot() performs steps. use demonstrated example dataset:","code":"library(hidecan) ## Getting an example dataset x <- get_example_data() hidecan_plot( gwas_list = x[[\"GWAS\"]], ## data-frame of GWAS results de_list = x[[\"DE\"]], ## data-frame of DE results can_list = x[[\"CAN\"]], ## data-frame of candidate genes score_thr_gwas = -log10(0.0001), ## sign. threshold for GWAS score_thr_de = -log10(0.05), ## sign. threshold for DE log2fc_thr = 0, ## log2FC threshold for DE label_size = 2 ## label size for candidate genes )"},{"path":"https://plantandfoodresearch.github.io/hidecan/index.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Create HIDECAN Plots for Visualising Genome-Wide Association Studies and Differential Expression Results","text":"using HIDECAN, please cite: Angelin-Bonnet, O., Vignes, M., Biggs, P. J., Baldwin, S., & Thomson, S. (2023). Visual integration GWAS differential expression results hidecan R package. bioRxiv, 2023-03. https://doi.org/10.1101/2023.03.30.535015","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CAN_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a CAN_data object — CAN_data","title":"Creates a CAN_data object — CAN_data","text":"Creates CAN_data object tibble data-frame candidate genes.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CAN_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a CAN_data object — CAN_data","text":"","code":"CAN_data(dat, keep_rownames_as = NULL)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CAN_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a CAN_data object — CAN_data","text":"dat Tibble, set candidate genes interest. See Details. keep_rownames_as Character, name column save rownames input data-frame. Default value NULL, .e. rownames discarded.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CAN_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a CAN_data object — CAN_data","text":"CAN_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CAN_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Creates a CAN_data object — CAN_data","text":"input data one row per gene, least following columns: chromosome: character column, chromosome gene located. start end: numeric, starting end position gene (bp). column position constructed middle value (mean) start end. name: character, name candidate genes displayed.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CAN_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a CAN_data object — CAN_data","text":"","code":"x <- get_example_data() CAN_data(x[[\"CAN\"]]) #> # A tibble: 32 × 7 #> id chromosome start end name gene_name position #> #> 1 PGSC0003DMG400003155 ST4.03ch03 46757152 46762127 4CL 4-coumar… 4.68e7 #> 2 PGSC0003DMG400014223 ST4.03ch03 57466692 57469946 4CL2 4-coumar… 5.75e7 #> 3 PGSC0003DMG400011189 ST4.03ch07 1001854 1006278 HQT HQT 1.00e6 #> 4 PGSC0003DMG400005492 ST4.03ch05 36342746 36347409 PAL phenylal… 3.63e7 #> 5 PGSC0003DMG400005279 ST4.03ch05 42523943 42525912 peroxi… peroxida… 4.25e7 #> 6 PGSC0003DMG400007782 ST4.03ch03 38537202 38540209 PHO1A PHO1A 3.85e7 #> 7 PGSC0003DMG400023182 ST4.03ch02 10091564 10093164 LIPIII… LipIII27 1.01e7 #> 8 PGSC0003DMG400029576  ST4.03ch08 45676042 45677832 PPOs Polyphen… 4.57e7 #> 9 PGSC0003DMG400018924 ST4.03ch08 45778567 45780333 NA Polyphen… 4.58e7 #> 10 PGSC0003DMG400018919 ST4.03ch08 45793661 45794229 NA Polyphen… 4.58e7 #> # ℹ 22 more rows"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/DE_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a DE_data object — DE_data","title":"Creates a DE_data object — DE_data","text":"Creates DE_data object tibble data-frame differential expression results.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/DE_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a DE_data object — DE_data","text":"","code":"DE_data(dat, keep_rownames_as = NULL)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/DE_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a DE_data object — DE_data","text":"dat Tibble, results differential expression analysis. See Details. keep_rownames_as Character, name column save rownames input data-frame. Default value NULL, .e. rownames discarded.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/DE_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a DE_data object — DE_data","text":"DE_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/DE_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Creates a DE_data object — DE_data","text":"input data one row per gene transcript, least following columns: chromosome: character column, chromosome gene/transcript located. start end: numeric, starting end position gene/transcript (bp). column position constructed middle value (mean) start end. score padj: numeric, DE score adjusted p-value gene/transcript. column score column missing, constructed -log10(padj). foldChange log2FoldChange: numeric, fold-change log2(fold-change) gene/transcript. column log2FoldChange missing, constructed log2(foldChange).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/DE_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a DE_data object — DE_data","text":"","code":"x <- get_example_data() DE_data(x[[\"DE\"]]) #> # A tibble: 10,671 × 9 #> gene chromosome padj log2FoldChange start end label score position #> #> 1 PGSC00… ST4.03ch00 0.787 0.0114 4.58e7 4.58e7 Prot… 0.104 4.58e7 #> 2 PGSC00… ST4.03ch01 0.630 0.00529 8.86e7 8.86e7 PhD-… 0.201 8.86e7 #> 3 PGSC00… ST4.03ch02 0.864 0.00362 4.86e7 4.86e7 Acet… 0.0637 4.86e7 #> 4 PGSC00… ST4.03ch03 0.530 0.0320 6.23e7 6.23e7 Phos… 0.276 6.23e7 #> 5 PGSC00… ST4.03ch04 0.975 0.00225 7.22e7 7.22e7 Cons… 0.0109 7.22e7 #> 6 PGSC00… ST4.03ch05 NA -0.000726 5.20e7 5.20e7 Cons… NA 5.20e7 #> 7 PGSC00… ST4.03ch06 0.844 -0.00323 5.95e7 5.95e7 30S … 0.0739 5.95e7 #> 8 PGSC00… ST4.03ch07 0.944 -0.00337 5.67e7 5.67e7 Ent-… 0.0252 5.67e7 #> 9 PGSC00… ST4.03ch08 0.403 0.0290 5.68e7 5.68e7 B3 d… 0.394 5.68e7 #> 10 PGSC00… ST4.03ch09 NA -0.000241 6.15e7 6.15e7 Cons… NA 6.15e7 #> # ℹ 10,661 more rows"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a GWAS_data object — GWAS_data","title":"Creates a GWAS_data object — GWAS_data","text":"Creates GWAS_data object tibble data-frame GWAS results.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a GWAS_data object — GWAS_data","text":"","code":"GWAS_data(dat, keep_rownames_as = NULL)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a GWAS_data object — GWAS_data","text":"dat Tibble, results GWAS analysis. See Details. keep_rownames_as Character, name column save rownames input data-frame. Default value NULL, .e. rownames discarded.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a GWAS_data object — GWAS_data","text":"GWAS_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Creates a GWAS_data object — GWAS_data","text":"input data one row per marker, least following columns: chromosome: character column, chromosome marker located. position: numeric, physical position marker along chromosome (bp). score padj: numeric, GWAS score adjusted p-value marker. column score column missing, constructed -log10(padj).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a GWAS_data object — GWAS_data","text":"","code":"x <- get_example_data() GWAS_data(x[[\"GWAS\"]]) #> # A tibble: 35,481 × 4 #> id chromosome position score #> #> 1 ST4.03ch00_45467783 ST4.03ch00 45467783 0.191 #> 2 ST4.03ch01_88589716 ST4.03ch01 88589716 1.84 #> 3 ST4.03ch02_48614228 ST4.03ch02 48614228 0.381 #> 4 ST4.03ch03_62263578 ST4.03ch03 62263578 0.661 #> 5 ST4.03ch04_72139135 ST4.03ch04 72139135 0.640 #> 6 ST4.03ch05_52040302 ST4.03ch05 52040302 0.346 #> 7 ST4.03ch06_59434834 ST4.03ch06 59434834 1.13 #> 8 ST4.03ch07_56713057 ST4.03ch07 56713057 0.213 #> 9 ST4.03ch08_56937627 ST4.03ch08 56937627 0.843 #> 10 ST4.03ch09_61537423 ST4.03ch09 61537423 0.512 #> # ℹ 35,471 more rows"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data_from_gwaspoly.html","id":null,"dir":"Reference","previous_headings":"","what":"Extracts information from GWASpoly output — GWAS_data_from_gwaspoly","title":"Extracts information from GWASpoly output — GWAS_data_from_gwaspoly","text":"Extracts GWAS results chromosome length GWASpoly output.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data_from_gwaspoly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extracts information from GWASpoly output — GWAS_data_from_gwaspoly","text":"","code":"GWAS_data_from_gwaspoly(gwaspoly_output, traits = NULL, models = NULL)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data_from_gwaspoly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extracts information from GWASpoly output — GWAS_data_from_gwaspoly","text":"gwaspoly_output GWASpoly.fitted GWASpoly.thresh object (returned GWASpoly::GWASpoly() GWASpoly::set.threshold() functions). traits Character vector, traits GWAS results extracted. NULL (default value), traits present considered. models Character vector, genetic models GWAS results extracted. NULL (default value), genetic models present considered.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data_from_gwaspoly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extracts information from GWASpoly output — GWAS_data_from_gwaspoly","text":"list following elements: gwas_data_list: named list GWAS_data objects, giving markers score possible trait/genetic model combination. names list form trait (genetic model). gwas_data_thr_list: input data GWASpoly.thresh object (GWASpoly::set.threshold() function), named list GwAS_data_thr, significant markers score possible trait/genetic model combination. names list form trait (genetic model). chrom_length: tibble one row per chromosome, giving length (bp) chromosome.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/apply_threshold.html","id":null,"dir":"Reference","previous_headings":"","what":"Filters GWAS or DE results based on a threshold — apply_threshold","title":"Filters GWAS or DE results based on a threshold — apply_threshold","text":"Filters markers genes/transcripts based threshold applied GWAS DE score, log2(fold-change) (applicable). set candidate genes, simply returns list. Note markers genes missing score log2(fold-change) removed dataset.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/apply_threshold.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filters GWAS or DE results based on a threshold — apply_threshold","text":"","code":"apply_threshold(x, score_thr = 0, log2fc_thr = 0) # S3 method for class 'GWAS_data' apply_threshold(x, score_thr = 0, log2fc_thr = 0) # S3 method for class 'DE_data' apply_threshold(x, score_thr = 0, log2fc_thr = 0) # S3 method for class 'CAN_data' apply_threshold(x, score_thr = 0, log2fc_thr = 0) # Default S3 method apply_threshold(x, score_thr = 0, log2fc_thr = 0)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/apply_threshold.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filters GWAS or DE results based on a threshold — apply_threshold","text":"x Either GWAS_data, DE_data CAN_data object. score_thr Numeric, threshold use markers' genes/transcripts' score. markers genes score equal higher threshold retained. Default value 0. Ignored CAN_data. log2fc_thr Numeric, threshold use absolute value genes/ transcripts' log2(fold-change). genes/transcripts absolute log2(fold-change) equal higher threshold retained. Ignored GWAS_data CAN_data.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/apply_threshold.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filters GWAS or DE results based on a threshold — apply_threshold","text":"filtered tibble (class GWAS_data_thr, DE_data_thr CAN_data_thr).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/apply_threshold.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Filters GWAS or DE results based on a threshold — apply_threshold","text":"","code":"x <- get_example_data() ## For GWAS results apply_threshold(GWAS_data(x[[\"GWAS\"]]), score_thr = 4) #> # A tibble: 37 × 4 #> id chromosome position score #> #> 1 ST4.03ch00_22680252 ST4.03ch00 22680252 4.41 #> 2 ST4.03ch01_6317643 ST4.03ch01 6317643 4.15 #> 3 ST4.03ch01_7671100 ST4.03ch01 7671100 4.43 #> 4 ST4.03ch01_8653747 ST4.03ch01 8653747 4.69 #> 5 ST4.03ch01_12842648 ST4.03ch01 12842648 6.85 #> 6 ST4.03ch01_13334335 ST4.03ch01 13334335 5.24 #> 7 ST4.03ch01_13544786 ST4.03ch01 13544786 4.00 #> 8 ST4.03ch01_42743974 ST4.03ch01 42743974 4.00 #> 9 ST4.03ch01_42949112 ST4.03ch01 42949112 4.18 #> 10 ST4.03ch01_52529264 ST4.03ch01 52529264 4.85 #> # ℹ 27 more rows ## For DE results - in second line, no threshold is applied ## on the log2(fold-change) apply_threshold(DE_data(x[[\"DE\"]]), score_thr = -log10(0.05), log2fc_thr = 1) #> # A tibble: 5 × 9 #> gene chromosome padj log2FoldChange start end label score position #> #> 1 PGSC0003D… ST4.03ch01 0.0488 1.61 8.15e7 8.15e7 Gene… 1.31 8.15e7 #> 2 PGSC0003D… ST4.03ch03 0.0488 1.14 3.49e7 3.49e7 Gene… 1.31 3.49e7 #> 3 PGSC0003D… ST4.03ch03 0.0184 3.06 5.99e7 5.99e7 Phos… 1.73 5.99e7 #> 4 PGSC0003D… ST4.03ch05 0.0414 1.10 3.47e6 3.47e6 Cons… 1.38 3.47e6 #> 5 PGSC0003D… ST4.03ch09 0.0328 1.51 5.40e7 5.40e7 Vici… 1.48 5.40e7 apply_threshold(DE_data(x[[\"DE\"]]), score_thr = -log10(0.05), log2fc_thr = 0) #> # A tibble: 57 × 9 #> gene chromosome padj log2FoldChange start end label score position #> #> 1 PGSC000… ST4.03ch00 0.0488 0.838 3.80e7 3.80e7 Pept… 1.31 3.80e7 #> 2 PGSC000… ST4.03ch01 0.0362 -0.181 5.83e7 5.83e7 Cons… 1.44 5.83e7 #> 3 PGSC000… ST4.03ch01 0.0488 1.61 8.15e7 8.15e7 Gene… 1.31 8.15e7 #> 4 PGSC000… ST4.03ch01 0.00465 0.438 8.45e7 8.45e7 Phi-2 2.33 8.45e7 #> 5 PGSC000… ST4.03ch02 0.0488 0.325 2.26e7 2.26e7 Cons… 1.31 2.26e7 #> 6 PGSC000… ST4.03ch02 0.0266 0.768 3.32e7 3.32e7 Leuc… 1.58 3.32e7 #> 7 PGSC000… ST4.03ch02 0.0488 0.381 4.14e7 4.14e7 Cons… 1.31 4.14e7 #> 8 PGSC000… ST4.03ch02 0.0314 0.663 4.23e7 4.23e7 Home… 1.50 4.23e7 #> 9 PGSC000… ST4.03ch03 0.0488 -0.804 5.33e5 5.41e5 SNF2… 1.31 5.37e5 #> 10 PGSC000… ST4.03ch03 0.0493 -0.345 9.26e6 9.26e6 Dihy… 1.31 9.26e6 #> # ℹ 47 more rows ## No effect on the Candidate genes apply_threshold(CAN_data(x[[\"CAN\"]])) #> # A tibble: 32 × 7 #> id chromosome start end name gene_name position #> #> 1 PGSC0003DMG400003155 ST4.03ch03 46757152 46762127 4CL 4-coumar… 4.68e7 #> 2 PGSC0003DMG400014223 ST4.03ch03 57466692 57469946 4CL2 4-coumar… 5.75e7 #> 3 PGSC0003DMG400011189 ST4.03ch07 1001854 1006278 HQT HQT 1.00e6 #> 4 PGSC0003DMG400005492 ST4.03ch05 36342746 36347409 PAL phenylal… 3.63e7 #> 5 PGSC0003DMG400005279 ST4.03ch05 42523943 42525912 peroxi… peroxida… 4.25e7 #> 6 PGSC0003DMG400007782 ST4.03ch03 38537202 38540209 PHO1A PHO1A 3.85e7 #> 7 PGSC0003DMG400023182 ST4.03ch02 10091564 10093164 LIPIII… LipIII27 1.01e7 #> 8 PGSC0003DMG400029576  ST4.03ch08 45676042 45677832 PPOs Polyphen… 4.57e7 #> 9 PGSC0003DMG400018924 ST4.03ch08 45778567 45780333 NA Polyphen… 4.58e7 #> 10 PGSC0003DMG400018919 ST4.03ch08 45793661 45794229 NA Polyphen… 4.58e7 #> # ℹ 22 more rows"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/combine_chrom_length.html","id":null,"dir":"Reference","previous_headings":"","what":"Computes chromosomes' length from list — combine_chrom_length","title":"Computes chromosomes' length from list — combine_chrom_length","text":"Computes length (bp) chromosome list GWAS DE results well candidate gene lists.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/combine_chrom_length.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Computes chromosomes' length from list — combine_chrom_length","text":"","code":"combine_chrom_length(x)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/combine_chrom_length.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Computes chromosomes' length from list — combine_chrom_length","text":"x list GWAS_data, DE_data CAN_data objects.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/combine_chrom_length.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Computes chromosomes' length from list — combine_chrom_length","text":"tibble two columns: chromosome (chromosome name) length (chromosome length base pair).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/combine_chrom_length.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Computes chromosomes' length from list — combine_chrom_length","text":"","code":"x <- get_example_data() y <- list(\"GWAS\" = GWAS_data(x[[\"GWAS\"]]), \"DE\" = DE_data(x[[\"DE\"]]), \"CAN\" = CAN_data(x[[\"CAN\"]])) combine_chrom_length(y) #> # A tibble: 13 × 2 #> chromosome length #> #> 1 ST4.03ch00 45813526 #> 2 ST4.03ch01 88627702 #> 3 ST4.03ch02 48614228 #> 4 ST4.03ch03 62263578 #> 5 ST4.03ch04 72170119 #> 6 ST4.03ch05 52040326 #> 7 ST4.03ch06 59476545 #> 8 ST4.03ch07 56715111 #> 9 ST4.03ch08 56937627 #> 10 ST4.03ch09 61539681 #> 11 ST4.03ch10 59687482 #> 12 ST4.03ch11 45409456 #> 13 ST4.03ch12 61152223"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/compute_chrom_length.html","id":null,"dir":"Reference","previous_headings":"","what":"Computes chromosomes' length — compute_chrom_length","title":"Computes chromosomes' length — compute_chrom_length","text":"Computes length (bp) chromosome maximum position markers genes chromosome.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/compute_chrom_length.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Computes chromosomes' length — compute_chrom_length","text":"","code":"compute_chrom_length(x) # S3 method for class 'GWAS_data' compute_chrom_length(x) # S3 method for class 'DE_data' compute_chrom_length(x) # S3 method for class 'CAN_data' compute_chrom_length(x)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/compute_chrom_length.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Computes chromosomes' length — compute_chrom_length","text":"x Either GWAS_data, DE_data CAN_data object.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/compute_chrom_length.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Computes chromosomes' length — compute_chrom_length","text":"tibble two columns: chromosome (chromosome name) length (chromosome length base pair).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/compute_chrom_length.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Computes chromosomes' length — compute_chrom_length","text":"","code":"x <- get_example_data() compute_chrom_length(GWAS_data(x[[\"GWAS\"]])) #> # A tibble: 13 × 2 #> chromosome length #> #> 1 ST4.03ch00 45467783 #> 2 ST4.03ch01 88589716 #> 3 ST4.03ch02 48614228 #> 4 ST4.03ch03 62263578 #> 5 ST4.03ch04 72139135 #> 6 ST4.03ch05 52040302 #> 7 ST4.03ch06 59434834 #> 8 ST4.03ch07 56713057 #> 9 ST4.03ch08 56937627 #> 10 ST4.03ch09 61537423 #> 11 ST4.03ch10 59687482 #> 12 ST4.03ch11 45409344 #> 13 ST4.03ch12 61148638 compute_chrom_length(DE_data(x[[\"DE\"]])) #> # A tibble: 13 × 2 #> chromosome length #> #> 1 ST4.03ch00 45813526 #> 2 ST4.03ch01 88627702 #> 3 ST4.03ch02 48578978 #> 4 ST4.03ch03 62258929 #> 5 ST4.03ch04 72170119 #> 6 ST4.03ch05 52040326 #> 7 ST4.03ch06 59476545 #> 8 ST4.03ch07 56715111 #> 9 ST4.03ch08 56849780 #> 10 ST4.03ch09 61539681 #> 11 ST4.03ch10 59684952 #> 12 ST4.03ch11 45409456 #> 13 ST4.03ch12 61152223 compute_chrom_length(CAN_data(x[[\"CAN\"]])) #> # A tibble: 7 × 2 #> chromosome length #> #> 1 ST4.03ch02 44537572 #> 2 ST4.03ch03 57469946 #> 3 ST4.03ch04 63041935 #> 4 ST4.03ch05 42525912 #> 5 ST4.03ch07 51457407 #> 6 ST4.03ch08 45907390 #> 7 ST4.03ch12 55092326"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/create_hidecan_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a HIDECAN plot — create_hidecan_plot","title":"Creates a HIDECAN plot — create_hidecan_plot","text":"Creates HIDECAN plot list filtered GWAS DE results /candidate genes.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/create_hidecan_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a HIDECAN plot — create_hidecan_plot","text":"","code":"create_hidecan_plot( x, chrom_length, colour_genes_by_score = TRUE, remove_empty_chrom = FALSE, chroms = NULL, chrom_limits = NULL, title = NULL, subtitle = NULL, n_rows = NULL, n_cols = 2, legend_position = \"bottom\", point_size = 3, label_size = 3.5, label_padding = 0.15 )"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/create_hidecan_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a HIDECAN plot — create_hidecan_plot","text":"x list GWAS_data_thr, DE_data_thr /CAN_data_thr produced apply_threshold() function. named, names appended y-axis labels (use ' ' empty name list). chrom_length Tibble columns chromosome length, giving chromosome length bp (see combine_chrom_length() function). colour_genes_by_score Logical, whether colour genes score (TRUE) log2(fold-change) (FALSE). Default value TRUE. remove_empty_chrom Logical, chromosomes significant markers/genes candidate genes removed plot? Default value FALSE. chroms Character vector, name chromosomes include plot. NULL (default value), chromosomes included. chrom_limits Integer vector length 2, named list elements integer vectors length 2. vector, gives lower upper limit chromosomes (bp) use plot. named list, names correspond chromosome names. Gives chromosome lower upper limits (bp) use plot. specified chromosomes. Default value NULL, .e. limits applied chromosomes (plotted entirety). title Character, title plot. Default value NULL (.e. title added plot). subtitle Character, subtitle plot. Default value NULL (.e. subtitle added plot). n_rows Integer, number rows chromosomes create plot. Default value NULL. n_cols Integer, number columns chromosomes create plot. Default value 2. set NULL n_rows NULL. legend_position Character, position legend plot. Can bottom (default value), top, right, left none. point_size Numeric, size points plot. Default value 3. label_size Numeric, size gene labels plot. Default value 3.5 (geom_label_repel). label_padding Numeric, amount padding around gene labels plot, unit number. Default value 0.15 (geom_label_repel).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/create_hidecan_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a HIDECAN plot — create_hidecan_plot","text":"ggplot.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/create_hidecan_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a HIDECAN plot — create_hidecan_plot","text":"","code":"if (interactive()) { x <- get_example_data() y <- list(\"GWAS\" = GWAS_data(x[[\"GWAS\"]]), \"DE\" = DE_data(x[[\"DE\"]]), \"CAN\" = CAN_data(x[[\"CAN\"]])) chrom_length <- combine_chrom_length(y) z <- list( apply_threshold(y[[\"GWAS\"]], score_thr = 4), apply_threshold(y[[\"DE\"]], score_thr = 1.3, log2fc_thr = 0.5), apply_threshold(y[[\"CAN\"]]) ) create_hidecan_plot(z, chrom_length, label_size = 2) ## Colour genes according to their fold-change create_hidecan_plot(z, chrom_length, colour_genes_by_score = FALSE, label_size = 2) ## Add names to the datasets create_hidecan_plot(setNames(z, c(\"Genomics\", \"RNAseq\", \"My list\")), chrom_length, colour_genes_by_score = FALSE, label_size = 2) ## Add names to some of the datasets only (e.g. not for GWAS results) create_hidecan_plot(setNames(z, c(\" \", \"RNAseq\", \"My list\")), chrom_length, colour_genes_by_score = FALSE, label_size = 2) ## Set limits on all chromosomes (to \"zoom in\" to the 10-20Mb region) create_hidecan_plot(z, chrom_length, label_size = 2, chrom_limits = c(10e6, 20e6)) ## Set limits on some chromosomes only create_hidecan_plot(z, chrom_length, label_size = 2, chrom_limits = list(\"ST4.03ch00\" = c(10e6, 20e6), \"ST4.03ch02\" = c(15e6, 25e6))) }"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-check_cols.html","id":null,"dir":"Reference","previous_headings":"","what":"Checks whether some columns are present in a tibble — .check_cols","title":"Checks whether some columns are present in a tibble — .check_cols","text":"Checks whether columns present tibble","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-check_cols.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Checks whether some columns are present in a tibble — .check_cols","text":"","code":".check_cols(x, col_names, param_name = \"Input data-frame\")"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-check_cols.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Checks whether some columns are present in a tibble — .check_cols","text":"x Tibble col_names character vector column names param_name Character, name dataframe use error message.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-check_cols.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Checks whether some columns are present in a tibble — .check_cols","text":"invisible NULL","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-compute_chrom_length_genes.html","id":null,"dir":"Reference","previous_headings":"","what":"Computes chromosomes' length for a tibble of genes — .compute_chrom_length_genes","title":"Computes chromosomes' length for a tibble of genes — .compute_chrom_length_genes","text":"Computes length (bp) chromosome maximum position genes chromosome.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-compute_chrom_length_genes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Computes chromosomes' length for a tibble of genes — .compute_chrom_length_genes","text":"","code":".compute_chrom_length_genes(x)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-compute_chrom_length_genes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Computes chromosomes' length for a tibble of genes — .compute_chrom_length_genes","text":"x Either DE_data CAN_data object.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-compute_chrom_length_genes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Computes chromosomes' length for a tibble of genes — .compute_chrom_length_genes","text":"tibble two columns: chromosome (chromosome name) length (chromosome length base pair).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/get_example_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Example dataset — get_example_data","title":"Example dataset — get_example_data","text":"Returns list example datasets.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/get_example_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Example dataset — get_example_data","text":"","code":"get_example_data()"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/get_example_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Example dataset — get_example_data","text":"list following elements: GWAS: tibble GWAS results, columns id, chromosome, position score. DE: tibble differential expression results, columns gene, chromosome, padj, log2FoldChange, start, end label. CAN: tibble candidate genes, columns id, chromosome, start, end, name gene_name.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/get_example_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Example dataset — get_example_data","text":"dataset used example presented : Angelin-Bonnet et al., BMC Plant Biology (2023). study, tetraploid potato plants half-sibling breeding population used assess genetic components tuber bruising. Capture sequencing used obtain genomic information individuals, genome-wide association study (GWAS) performed 72,847 genomic biallelic variants obtained 158 plants bruising score measured. GWAS analysis carried GWASpoly package. addition, expression data obtained 25,163 transcribed genes, differential expression (DE) analysis carried 41 low- 33 high-bruising samples. Finally, literature search yielded list 42 candidate genes identified previous studies involved potato tuber bruising mechanisms. subset GWAS DE results, well list candidate genes literature, made available function. complete GWAS results table, half genomic variants GWAS score < 3.5 randomly selected consequently discarded, yielding dataset GWAS scores 35,481 variants. Similarly, half transcribed genes DE results table adjusted p-value > 0.05 randomly selected discarded, yielding dataset DE results 10,671 transcribed genes. filtering performed reduce size datasets (accordance CRAN policies), ensures significant markers genes retained datasets. Finally, candidate genes located chromosome 3 removed example dataset better clarity resulting HIDECAN plot, leaving 32 candidate genes.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Wrapper to create a HIDECAN plot — hidecan_plot","title":"Wrapper to create a HIDECAN plot — hidecan_plot","text":"Wrapper function create HIDECAN plot GWAS results, DE results candidate genes.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Wrapper to create a HIDECAN plot — hidecan_plot","text":"","code":"hidecan_plot( gwas_list = NULL, de_list = NULL, can_list = NULL, score_thr_gwas = 4, score_thr_de = 2, log2fc_thr = 1, chrom_length = NULL, colour_genes_by_score = TRUE, remove_empty_chrom = FALSE, chroms = NULL, chrom_limits = NULL, title = NULL, subtitle = NULL, n_rows = NULL, n_cols = 2, legend_position = \"bottom\", point_size = 3, label_size = 3.5, label_padding = 0.15 )"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Wrapper to create a HIDECAN plot — hidecan_plot","text":"gwas_list Data-frame list data-frames containing GWAS results, least chromosome, position either padj score columns. named list, names used plot. de_list Data-frame list data-frames containing DE results, least chromosome, start, end, log2FoldChange either padj score columns. named list, names used plot. can_list Data-frame list data-frames containing candidate genes, least chromosome, start, end name columns. named list, names used plot. score_thr_gwas Numeric, score threshold GWAS results used select markers plotted. Default value 4. score_thr_de Numeric, score threshold DE results used select markers plotted. Default value 2. log2fc_thr Numeric, log2(fold-change) threshold used select genes plotted. Default value 1. chrom_length Optional, tibble columns chromosome length, giving chromosome length bp. NULL (default), inferred GWAS, DE candidate gene data. colour_genes_by_score Logical, whether colour genes score (TRUE) log2(fold-change) (FALSE). Default value TRUE. remove_empty_chrom Logical, chromosomes significant markers/genes candidate genes removed plot? Default value FALSE. chroms Character vector, name chromosomes include plot. NULL (default value), chromosomes included. chrom_limits Integer vector length 2, named list elements integer vectors length 2. vector, gives lower upper limit chromosomes (bp) use plot. named list, names correspond chromosome names. Gives chromosome lower upper limits (bp) use plot. specified chromosomes. Default value NULL, .e. limits applied chromosomes (plotted entirety). title Character, title plot. Default value NULL (.e. title added plot). subtitle Character, subtitle plot. Default value NULL (.e. subtitle added plot). n_rows Integer, number rows chromosomes create plot. Default value NULL. n_cols Integer, number columns chromosomes create plot. Default value 2. set NULL n_rows NULL. legend_position Character, position legend plot. Can bottom (default value), top, right, left none. point_size Numeric, size points plot. Default value 3. label_size Numeric, size gene labels plot. Default value 3.5 (geom_label_repel). label_padding Numeric, amount padding around gene labels plot, unit number. Default value 0.15 (geom_label_repel).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Wrapper to create a HIDECAN plot — hidecan_plot","text":"ggplot.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Wrapper to create a HIDECAN plot — hidecan_plot","text":"","code":"if (interactive()) { x <- get_example_data() ## Typical example with one GWAs result table, one DE result table and ## one table of candidate genes hidecan_plot(gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.005), log2fc_thr = 0, label_size = 2) ## Example with two sets of GWAS results hidecan_plot(gwas_list = list(x[[\"GWAS\"]], x[[\"GWAS\"]]), score_thr_gwas = 4) ## Example with two sets of DE results, with names hidecan_plot(de_list = list(\"X vs Y\" = x[[\"DE\"]], \"X vs Z\" = x[[\"DE\"]]), score_thr_de = -log10(0.05), log2fc_thr = 0) ## Set limits on all chromosomes (to \"zoom in\" to the 10-20Mb region) hidecan_plot(gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.005), log2fc_thr = 0, label_size = 2, chrom_limits = c(10e6, 20e6)) ## Set limits on some chromosomes only hidecan_plot(gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.005), log2fc_thr = 0, label_size = 2, chrom_limits = list(\"ST4.03ch00\" = c(10e6, 20e6), \"ST4.03ch02\" = c(15e6, 25e6))) }"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot_from_gwaspoly.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a HIDECAN plot from GWASpoly output — hidecan_plot_from_gwaspoly","title":"Creates a HIDECAN plot from GWASpoly output — hidecan_plot_from_gwaspoly","text":"Creates HIDECAN plot GWAS results GWASpoly.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot_from_gwaspoly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a HIDECAN plot from GWASpoly output — hidecan_plot_from_gwaspoly","text":"","code":"hidecan_plot_from_gwaspoly(gwaspoly_output, traits = NULL, models = NULL, ...)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot_from_gwaspoly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a HIDECAN plot from GWASpoly output — hidecan_plot_from_gwaspoly","text":"gwaspoly_output GWASpoly.thresh object (returned GWASpoly::set.threshold() function). traits Character vector, traits GWAS results extracted. NULL (default value), traits present considered. models Character vector, genetic models GWAS results extracted. NULL (default value), genetic models present considered. ... arguments passed create_hidecan_plot() function.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot_from_gwaspoly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a HIDECAN plot from GWASpoly output — hidecan_plot_from_gwaspoly","text":"ggplot.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/manhattan_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a Manhattan plot — manhattan_plot","title":"Creates a Manhattan plot — manhattan_plot","text":"Creates Manhattan plot data-frame GWAS results.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/manhattan_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a Manhattan plot — manhattan_plot","text":"","code":"manhattan_plot( gwas_list, score_thr = NULL, chroms = NULL, title = NULL, subtitle = NULL, size_range = c(1, 3), chrom_col = NULL, ncol = NULL )"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/manhattan_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a Manhattan plot — manhattan_plot","text":"gwas_list Data-frame list data-frames containing GWAS results, least chromosome, position either padj score columns. named list, names used plot. score_thr Numeric, significance threshold GWAS score. value provided, represented Manhattan plot red dashed line. NULL (default value), significance threshold line drawn. chroms Character vector, name chromosomes include plot. NULL (default value), chromosomes included. title Character, title plot. Default value NULL (.e. title added plot). subtitle Character, subtitle plot. Default value NULL (.e. subtitle added plot). size_range Numeric vector length 2, minimum maximum point size plot. Points size proportional GWAS score. Default value c(1, 3). chrom_col Character vector colour names code, colours use draw points chromosome. Names ignored. vector provided contains less colours number chromosomes plot, values recycled. NULL, default, colours automatically chosen predefined palette. ncol Integer, number Manhattan plots per row several GWAS results provided.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/manhattan_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a Manhattan plot — manhattan_plot","text":"ggplot.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/manhattan_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a Manhattan plot — manhattan_plot","text":"","code":"if (interactive()){ x <- get_example_data()[[\"GWAS\"]] manhattan_plot(x) ## Adding a significance threshold line in the plot manhattan_plot(x, score_thr = 4) ## Use only two colours for the chromosomes manhattan_plot(x, score_thr = 4, chrom_col = c(\"dodgerblue1\", \"dodgerblue4\")) }"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_CAN_data.html","id":null,"dir":"Reference","previous_headings":"","what":"CAN_data constructor — new_CAN_data","title":"CAN_data constructor — new_CAN_data","text":"CAN_data constructor","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_CAN_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"CAN_data constructor — new_CAN_data","text":"","code":"new_CAN_data(dat)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_CAN_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"CAN_data constructor — new_CAN_data","text":"dat Tibble, containing information genes interest, least columns chromosome, start, end, position name.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_CAN_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"CAN_data constructor — new_CAN_data","text":"CAN_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_DE_data.html","id":null,"dir":"Reference","previous_headings":"","what":"DE_data constructor — new_DE_data","title":"DE_data constructor — new_DE_data","text":"DE_data constructor","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_DE_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"DE_data constructor — new_DE_data","text":"","code":"new_DE_data(dat)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_DE_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"DE_data constructor — new_DE_data","text":"dat Tibble, results differential expression analysis, least columns chromosome, score, log2FoldChange, start, end position.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_DE_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"DE_data constructor — new_DE_data","text":"DE_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_GWAS_data.html","id":null,"dir":"Reference","previous_headings":"","what":"GWAS_data constructor — new_GWAS_data","title":"GWAS_data constructor — new_GWAS_data","text":"GWAS_data constructor","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_GWAS_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"GWAS_data constructor — new_GWAS_data","text":"","code":"new_GWAS_data(dat)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_GWAS_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"GWAS_data constructor — new_GWAS_data","text":"dat Tibble, results GWAS analysis, least columns chromosome, position score.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_GWAS_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"GWAS_data constructor — new_GWAS_data","text":"GWAS_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/run_hidecan_shiny.html","id":null,"dir":"Reference","previous_headings":"","what":"Launches the HIDECAN shiny app — run_hidecan_shiny","title":"Launches the HIDECAN shiny app — run_hidecan_shiny","text":"Starts HIDECAN shiny app. app reads csv data produce HIDECAN plot.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/run_hidecan_shiny.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Launches the HIDECAN shiny app — run_hidecan_shiny","text":"","code":"run_hidecan_shiny()"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/run_hidecan_shiny.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Launches the HIDECAN shiny app — run_hidecan_shiny","text":"return value, called side effects (launching shiny app).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_CAN_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Checks validity of input for CAN_data constructor — validate_CAN_data","title":"Checks validity of input for CAN_data constructor — validate_CAN_data","text":"Checks validity input CAN_data constructor","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_CAN_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Checks validity of input for CAN_data constructor — validate_CAN_data","text":"","code":"validate_CAN_data(x)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_CAN_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Checks validity of input for CAN_data constructor — validate_CAN_data","text":"x, CAN_data object constructed via new_CAN_data.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_CAN_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Checks validity of input for CAN_data constructor — validate_CAN_data","text":"CAN_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_DE_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Checks validity of input for DE_data constructor — validate_DE_data","title":"Checks validity of input for DE_data constructor — validate_DE_data","text":"Checks validity input DE_data constructor","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_DE_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Checks validity of input for DE_data constructor — validate_DE_data","text":"","code":"validate_DE_data(x)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_DE_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Checks validity of input for DE_data constructor — validate_DE_data","text":"x, DE_data object constructed via new_DE_data.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_DE_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Checks validity of input for DE_data constructor — validate_DE_data","text":"DE_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_GWAS_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Checks validity of input for GWAS_data constructor — validate_GWAS_data","title":"Checks validity of input for GWAS_data constructor — validate_GWAS_data","text":"Checks validity input GWAS_data constructor","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_GWAS_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Checks validity of input for GWAS_data constructor — validate_GWAS_data","text":"","code":"validate_GWAS_data(x)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_GWAS_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Checks validity of input for GWAS_data constructor — validate_GWAS_data","text":"x, GWAS_data object constructed via new_GWAS_data.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_GWAS_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Checks validity of input for GWAS_data constructor — validate_GWAS_data","text":"GWAS_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/news/index.html","id":"hidecan-1109000","dir":"Changelog","previous_headings":"","what":"hidecan 1.1.0.9000","title":"hidecan 1.1.0.9000","text":"Added manhattan_plot() function generate Manhattan plots table GWAS results. Fixed bug specifying chromosome limits hidecan_plot_from_gwaspoly() mess ordering chromosomes plot.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/news/index.html","id":"hidecan-110","dir":"Changelog","previous_headings":"","what":"hidecan 1.1.0","title":"hidecan 1.1.0","text":"CRAN release: 2023-02-10 Removed get_gwaspoly_example_data() function package doesn’t depend GWASpoly (CRAN submission) Saved example object previously returned get_gwaspoly_example_data() rda file extdata folder","code":""}] +[{"path":"https://plantandfoodresearch.github.io/hidecan/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2023 hidecan authors Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan-step-by-step.html","id":"formatting-input-data","dir":"Articles","previous_headings":"","what":"Formatting input data","title":"Creating a HIDECAN plot step by step","text":"hood, hidecan package relies S3 classes, really just tibbles specific columns. constructors S3 classes perform series checks computations make sure required columns (chromosome, score, position) present data. GWAS results data-frames turned GWAS_data objects GWAS_data() constructor: DE results data-frames turned DE_data objects DE_data() constructor: Candidate genes data-frames turned CAN_data objects CAN_data() constructor: constructors throw error required column missing input data (e.g. chromosome column): also compute marker gene scores adjusted p-values necessary (see Input data section hidecan vignette). example, DE results, provide padj column (adjusted p-values genes) rather score column, constructor compute score column based padj column. can also notice position column computed based start end genes:","code":"gwas_data <- GWAS_data(x[[\"GWAS\"]]) class(gwas_data) #> [1] \"GWAS_data\" \"tbl_df\" \"tbl\" \"data.frame\" head(gwas_data) #> # A tibble: 6 × 4 #> id chromosome position score #> #> 1 ST4.03ch00_45467783 ST4.03ch00 45467783 0.191 #> 2 ST4.03ch01_88589716 ST4.03ch01 88589716 1.84 #> 3 ST4.03ch02_48614228 ST4.03ch02 48614228 0.381 #> 4 ST4.03ch03_62263578 ST4.03ch03 62263578 0.661 #> 5 ST4.03ch04_72139135 ST4.03ch04 72139135 0.640 #> 6 ST4.03ch05_52040302 ST4.03ch05 52040302 0.346 de_data <- DE_data(x[[\"DE\"]]) class(de_data) #> [1] \"DE_data\" \"tbl_df\" \"tbl\" \"data.frame\" head(de_data) #> # A tibble: 6 × 9 #> gene chromosome padj log2FoldChange start end label score position #> #> 1 PGSC000… ST4.03ch00 0.787 0.0114 4.58e7 4.58e7 Prot… 0.104 4.58e7 #> 2 PGSC000… ST4.03ch01 0.630 0.00529 8.86e7 8.86e7 PhD-… 0.201 8.86e7 #> 3 PGSC000… ST4.03ch02 0.864 0.00362 4.86e7 4.86e7 Acet… 0.0637 4.86e7 #> 4 PGSC000… ST4.03ch03 0.530 0.0320 6.23e7 6.23e7 Phos… 0.276 6.23e7 #> 5 PGSC000… ST4.03ch04 0.975 0.00225 7.22e7 7.22e7 Cons… 0.0109 7.22e7 #> 6 PGSC000… ST4.03ch05 NA -0.000726 5.20e7 5.20e7 Cons… NA 5.20e7 ## CAN_data constructor can_data <- CAN_data(x[[\"CAN\"]]) class(can_data) #> [1] \"CAN_data\" \"tbl_df\" \"tbl\" \"data.frame\" head(can_data) #> # A tibble: 6 × 7 #> id chromosome start end name gene_name position #> #> 1 PGSC0003DMG400003155 ST4.03ch03 46757152 46762127 4CL 4-coumar… 4.68e7 #> 2 PGSC0003DMG400014223 ST4.03ch03 57466692 57469946 4CL2 4-coumar… 5.75e7 #> 3 PGSC0003DMG400011189 ST4.03ch07 1001854 1006278 HQT HQT 1.00e6 #> 4 PGSC0003DMG400005492 ST4.03ch05 36342746 36347409 PAL phenylal… 3.63e7 #> 5 PGSC0003DMG400005279 ST4.03ch05 42523943 42525912 peroxida… peroxida… 4.25e7 #> 6 PGSC0003DMG400007782 ST4.03ch03 38537202 38540209 PHO1A PHO1A 3.85e7 gwas_wrong_input <- x[[\"GWAS\"]] |> select(-chromosome) GWAS_data(gwas_wrong_input) #> Error: Input data-frame is missing the following columns: 'chromosome'. ## Input tibble head(x[[\"DE\"]]) #> # A tibble: 6 × 7 #> gene chromosome padj log2FoldChange start end label #> #> 1 PGSC0003DMG400032056 ST4.03ch00 0.787 0.0114 45813195 45813526 Prote… #> 2 PGSC0003DMG400018039 ST4.03ch01 0.630 0.00529 88623473 88627702 PhD-f… #> 3 PGSC0003DMG400020231 ST4.03ch02 0.864 0.00362 48563271 48578978 Acety… #> 4 PGSC0003DMG400009197 ST4.03ch03 0.530 0.0320 62256322 62258929 Phosp… #> 5 PGSC0003DMG403025662 ST4.03ch04 0.975 0.00225 72168842 72170119 Conse… #> 6 PGSC0003DMG400023316 ST4.03ch05 NA -0.000726 52039916 52040326 Conse… ## Output of the DE_data constructor head(de_data) #> # A tibble: 6 × 9 #> gene chromosome padj log2FoldChange start end label score position #> #> 1 PGSC000… ST4.03ch00 0.787 0.0114 4.58e7 4.58e7 Prot… 0.104 4.58e7 #> 2 PGSC000… ST4.03ch01 0.630 0.00529 8.86e7 8.86e7 PhD-… 0.201 8.86e7 #> 3 PGSC000… ST4.03ch02 0.864 0.00362 4.86e7 4.86e7 Acet… 0.0637 4.86e7 #> 4 PGSC000… ST4.03ch03 0.530 0.0320 6.23e7 6.23e7 Phos… 0.276 6.23e7 #> 5 PGSC000… ST4.03ch04 0.975 0.00225 7.22e7 7.22e7 Cons… 0.0109 7.22e7 #> 6 PGSC000… ST4.03ch05 NA -0.000726 5.20e7 5.20e7 Cons… NA 5.20e7"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan-step-by-step.html","id":"computing-chromosome-length","dir":"Articles","previous_headings":"","what":"Computing chromosome length","title":"Creating a HIDECAN plot step by step","text":"input datasets formatted appropriately, used compute length chromosomes present data. done combine_chrom_length() function, applied list GWAS_data, DE_data CAN_data objects: function works calling element list compute_chrom_length() function. function, according whether input tibble markers (GWAS_data) genes (DE_data CAN_data), looks maximum value either position column (markers) end column (genes).","code":"chrom_length <- combine_chrom_length(list(gwas_data, de_data, can_data)) chrom_length #> # A tibble: 13 × 2 #> chromosome length #> #> 1 ST4.03ch00 45813526 #> 2 ST4.03ch01 88627702 #> 3 ST4.03ch02 48614228 #> 4 ST4.03ch03 62263578 #> 5 ST4.03ch04 72170119 #> 6 ST4.03ch05 52040326 #> 7 ST4.03ch06 59476545 #> 8 ST4.03ch07 56715111 #> 9 ST4.03ch08 56937627 #> 10 ST4.03ch09 61539681 #> 11 ST4.03ch10 59687482 #> 12 ST4.03ch11 45409456 #> 13 ST4.03ch12 61152223 head(compute_chrom_length(gwas_data), 3) #> # A tibble: 3 × 2 #> chromosome length #> #> 1 ST4.03ch00 45467783 #> 2 ST4.03ch01 88589716 #> 3 ST4.03ch02 48614228 head(compute_chrom_length(de_data), 3) #> # A tibble: 3 × 2 #> chromosome length #> #> 1 ST4.03ch00 45813526 #> 2 ST4.03ch01 88627702 #> 3 ST4.03ch02 48578978"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan-step-by-step.html","id":"applying-threshold","dir":"Articles","previous_headings":"","what":"Applying threshold","title":"Creating a HIDECAN plot step by step","text":"Next, GWAS DE results tibbles filtered according threshold, order retain significant markers genes. done apply_threshold() function. function two (rather self-explanatory) arguments: score_thr log2fc_thr. applied GWAS_data object, function filters markers score value set score_thr argument (log2fc_thr argument ignored), returns object class GWAS_data_thr: DE_data object, apply_threshold function filters genes based score log2(fold-change), returns object class DE_data_thr: Finally, applied CAN_data object, apply_threshold() function simply returns input tibble object class CAN_data_thr: GWAS_data, DE_data CAN_data objects, GWAS_data_thr, DE_data_thr CAN_data_thr objects really just tibbles.","code":"dim(gwas_data) #> [1] 35481 4 gwas_data_thr <- apply_threshold(gwas_data, score_thr = 4) class(gwas_data_thr) #> [1] \"GWAS_data_thr\" \"tbl_df\" \"tbl\" \"data.frame\" dim(gwas_data_thr) #> [1] 37 4 head(gwas_data_thr) #> # A tibble: 6 × 4 #> id chromosome position score #> #> 1 ST4.03ch00_22680252 ST4.03ch00 22680252 4.41 #> 2 ST4.03ch01_6317643 ST4.03ch01 6317643 4.15 #> 3 ST4.03ch01_7671100 ST4.03ch01 7671100 4.43 #> 4 ST4.03ch01_8653747 ST4.03ch01 8653747 4.69 #> 5 ST4.03ch01_12842648 ST4.03ch01 12842648 6.85 #> 6 ST4.03ch01_13334335 ST4.03ch01 13334335 5.24 dim(de_data) #> [1] 10671 9 de_data_thr <- apply_threshold(de_data, score_thr = 2, log2fc_thr = 0.5) class(de_data_thr) #> [1] \"DE_data_thr\" \"tbl_df\" \"tbl\" \"data.frame\" dim(de_data_thr) #> [1] 2 9 head(de_data_thr) #> # A tibble: 2 × 9 #> gene chromosome padj log2FoldChange start end label score position #> #> 1 PGSC0003… ST4.03ch10 0.00480 0.757 3.30e7 3.30e7 Cons… 2.32 3.30e7 #> 2 PGSC0003… ST4.03ch10 0.00305 0.691 5.82e7 5.82e7 N-ac… 2.52 5.82e7 dim(can_data) #> [1] 32 7 can_data_thr <- apply_threshold(can_data, score_thr = 2, log2fc_thr = 0.5) class(can_data_thr) #> [1] \"CAN_data_thr\" \"tbl_df\" \"tbl\" \"data.frame\" dim(can_data_thr) #> [1] 32 7 head(can_data_thr) #> # A tibble: 6 × 7 #> id chromosome start end name gene_name position #> #> 1 PGSC0003DMG400003155 ST4.03ch03 46757152 46762127 4CL 4-coumar… 4.68e7 #> 2 PGSC0003DMG400014223 ST4.03ch03 57466692 57469946 4CL2 4-coumar… 5.75e7 #> 3 PGSC0003DMG400011189 ST4.03ch07 1001854 1006278 HQT HQT 1.00e6 #> 4 PGSC0003DMG400005492 ST4.03ch05 36342746 36347409 PAL phenylal… 3.63e7 #> 5 PGSC0003DMG400005279 ST4.03ch05 42523943 42525912 peroxida… peroxida… 4.25e7 #> 6 PGSC0003DMG400007782 ST4.03ch03 38537202 38540209 PHO1A PHO1A 3.85e7"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan-step-by-step.html","id":"creating-the-hidecan-plot","dir":"Articles","previous_headings":"","what":"Creating the HIDECAN plot","title":"Creating a HIDECAN plot step by step","text":"Finally, filtered datasets combined list passed create_hidecan_plot() function, along tibble chromosome length. function generates HIDECAN ggplot: function shares arguments hidecan_plot() wrapper controlling different aspects plot.","code":"create_hidecan_plot( list(gwas_data_thr, de_data_thr, can_data_thr), chrom_length )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"input-data","dir":"Articles","previous_headings":"","what":"Input data","title":"hidecan","text":"hidecan package takes input tibbles (data-frames) GWAS DE results candidate genes. input data-frames contain mandatory columns, depending type data. list example input datasets can obtained via get_example_data() function:","code":"x <- get_example_data() str(x, max.level = 1) #> List of 3 #> $ GWAS: tibble [35,481 × 4] (S3: tbl_df/tbl/data.frame) #> $ DE : tibble [10,671 × 7] (S3: tbl_df/tbl/data.frame) #> $ CAN : tibble [32 × 6] (S3: tbl_df/tbl/data.frame)"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"gwas-results","dir":"Articles","previous_headings":"Input data","what":"GWAS results","title":"hidecan","text":"GWAS results provided tibble data-frame, one row per genetic marker. data-frame contain least following columns: chromosome: character column, giving ID chromosome marker located; position: numeric column, physical position along chromosome (base pairs - bp) marker; either score padj: numeric column, providing either score (.e. -log10(p-value)) adjusted p-value marker. score column provided, padj column ignored. padj column provided, score column constructed -log10(padj). column present data-frame ignored. example valid input shown :","code":"head(x[[\"GWAS\"]]) #> # A tibble: 6 × 4 #> id chromosome position score #> #> 1 ST4.03ch00_45467783 ST4.03ch00 45467783 0.191 #> 2 ST4.03ch01_88589716 ST4.03ch01 88589716 1.84 #> 3 ST4.03ch02_48614228 ST4.03ch02 48614228 0.381 #> 4 ST4.03ch03_62263578 ST4.03ch03 62263578 0.661 #> 5 ST4.03ch04_72139135 ST4.03ch04 72139135 0.640 #> 6 ST4.03ch05_52040302 ST4.03ch05 52040302 0.346"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"differential-expression-results","dir":"Articles","previous_headings":"Input data","what":"Differential expression results","title":"hidecan","text":"DE results provided tibble data-frame, one row per gene. data-frame contain least following columns: chromosome: character column, giving ID chromosome gene located; start end: numeric columns, giving starting end position gene along chromosome (bp). two columns used calculate position gene half-way point start end gene. either score padj: numeric column, providing either score (.e. -log10(p-value)) adjusted p-value gene. score column provided, padj column ignored. padj column provided, score column constructed -log10(padj). either foldChange log2FoldChange: numeric column, giving either fold-change log2(fold-change) gene. log2FoldChange column provided, foldChange column ignored. foldChange column provided, log2FoldChange constructed log2(foldChange). column present data-frame ignored. example valid input shown : (Note example dataset, genes missing values padj column; corresponds genes filtered via independent filtering DESeq2 package).","code":"head(x[[\"DE\"]]) #> # A tibble: 6 × 7 #> gene chromosome padj log2FoldChange start end label #> #> 1 PGSC0003DMG400032056 ST4.03ch00 0.787 0.0114 45813195 45813526 Prote… #> 2 PGSC0003DMG400018039 ST4.03ch01 0.630 0.00529 88623473 88627702 PhD-f… #> 3 PGSC0003DMG400020231 ST4.03ch02 0.864 0.00362 48563271 48578978 Acety… #> 4 PGSC0003DMG400009197 ST4.03ch03 0.530 0.0320 62256322 62258929 Phosp… #> 5 PGSC0003DMG403025662 ST4.03ch04 0.975 0.00225 72168842 72170119 Conse… #> 6 PGSC0003DMG400023316 ST4.03ch05 NA -0.000726 52039916 52040326 Conse…"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"candidate-genes","dir":"Articles","previous_headings":"Input data","what":"Candidate genes","title":"hidecan","text":"list candidate genes (e.g. genes previously found associated trait interest based literature search) can provided tibble data-frame, one row per gene. data-frame can also contain variants interest (see ). data-frame contain least following columns: chromosome: character column, giving ID chromosome gene located; start end: numeric columns, giving starting end position gene along chromosome (bp). two columns used calculate position gene half-way point start end gene. genomic variants markers, simply set start end columns physical position marker. name: character column, giving name candidate gene displayed HIDECAN plot. Set NA subset genes remove label plot (can help many genes close, avoid cluttering plot). column present data-frame ignored. example valid input shown :","code":"head(x[[\"CAN\"]]) #> # A tibble: 6 × 6 #> id chromosome start end name gene_name #> #> 1 PGSC0003DMG400003155 ST4.03ch03 46757152 46762127 4CL 4-coumarate-CoA … #> 2 PGSC0003DMG400014223 ST4.03ch03 57466692 57469946 4CL2 4-coumarate-CoA … #> 3 PGSC0003DMG400011189 ST4.03ch07 1001854 1006278 HQT HQT #> 4 PGSC0003DMG400005492 ST4.03ch05 36342746 36347409 PAL phenylalanine am… #> 5 PGSC0003DMG400005279 ST4.03ch05 42523943 42525912 peroxidase peroxidase #> 6 PGSC0003DMG400007782 ST4.03ch03 38537202 38540209 PHO1A PHO1A"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"creating-a-hidecan-plot","dir":"Articles","previous_headings":"","what":"Creating a HIDECAN plot","title":"hidecan","text":"hidecan_plot() function creates HIDECAN plot. takes input data-frames presented , well score log2(fold-change) thresholds used select significant markers genes. example, show markers score 4, corresponds p-value 1×10−41\\times10^{-4}, genes score 1.3, corresponds p-value 0.05. don’t place threshold log2(fold-change) genes: Note possible provide subset possible input data, e.g. GWAS results list candidate genes:","code":"hidecan_plot( gwas_list = x[[\"GWAS\"]], ## data-frame of GWAS results de_list = x[[\"DE\"]], ## data-frame of DE results can_list = x[[\"CAN\"]], ## data-frame of candidate genes score_thr_gwas = -log10(0.0001), ## sign. threshold for GWAS score_thr_de = -log10(0.05), ## sign. threshold for DE log2fc_thr = 0 ## log2FC threshold for DE ) hidecan_plot( gwas_list = x[[\"GWAS\"]], can_list = x[[\"CAN\"]], score_thr_gwas = 4 )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"removing-empty-chromosomes","dir":"Articles","previous_headings":"","what":"Removing empty chromosomes","title":"hidecan","text":"default, HIDECAN plot shows chromosomes present input data. However, possible chromosomes appear empty, contain significant gene marker, candidate gene. case, possible exclude “empty” chromosomes HIDECAN plot, remove_empty_chrom argument. demonstrate increasing score threshold applied GWAS results, order get fewer significant markers. case, chromosomes 0, 6, 9 10 contain significant marker gene interest: setting remove_empty_chrom argument TRUE, chromosomes removed plot:","code":"## Chromosomes 0, 6, 9 and 10 are empty hidecan_plot( gwas_list = x[[\"GWAS\"]], can_list = x[[\"CAN\"]], score_thr_gwas = 5 ) hidecan_plot( gwas_list = x[[\"GWAS\"]], can_list = x[[\"CAN\"]], score_thr_gwas = 5, remove_empty_chrom = TRUE )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"selecting-chromosomes-and-genomic-positions","dir":"Articles","previous_headings":"","what":"Selecting chromosomes and genomic positions","title":"hidecan","text":"possible specify chromosomes represented HIDECAN plot, via chroms argument. example, following command restrict plot chromosomes 7 8: can also “zoom ” chromosomes, chrom_limits argument. zoom chromosomes , pass chrom_limits argument integer vector length 2, gives lower upper limits bp use. example , focus 10-20Mb region chromosome: Alternatively, can apply different limits chromosomes, passing named list argument. names list match chromosomes name, element integer vector length 2 giving lower upper limits bp use corresponding chromosome. example, focus 10-20Mb region chromosome 1, 30-40Mb region chromosome 5, leave chromosomes : two options chroms chrom_limits can used together:","code":"hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, chroms = c(\"ST4.03ch07\", \"ST4.03ch08\") ) hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, chrom_limits = c(10e6, 20e6) ) hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, chrom_limits = list(\"ST4.03ch01\" = c(10e6, 20e6), \"ST4.03ch05\" = c(30e6, 40e6)) ) hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, chroms = c(\"ST4.03ch07\", \"ST4.03ch08\"), chrom_limits = list(\"ST4.03ch07\" = c(50e6, 55e6), \"ST4.03ch08\" = c(45e6, 50e6)) )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"colour-genes-by-log2fold-change","dir":"Articles","previous_headings":"","what":"Colour genes by log2(fold-change)","title":"hidecan","text":"default, HIDECAN plot, points representing significant markers DE genes coloured according GWAS/DE score. However, possible colour DE genes log2(fold-change) value instead, setting colour_genes_by_score argument FALSE: Genes negative log2(fold-change) represented shade blue, genes positive log2(fold-change) represented shade red.","code":"hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, colour_genes_by_score = FALSE )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"more-than-one-gwas-de-or-candidate-gene-list","dir":"Articles","previous_headings":"","what":"More than one GWAS, DE or candidate gene list","title":"hidecan","text":"hidecan_plot() function can take input lists data-frames GWAS results, DE results candidate genes. way, possible visualise one GWAS DE analyses , example investigating several traits comparing two treatment groups. example, ’ll focus chromosomes 7 8 (clarity plot): ’ll create second data-frame GWAS results shuffling marker scores example dataset: can pass GWAS results data-frames hidecan_plot() function list: default, two GWAS tracks given unique y-axis labels, can seen . possible customise naming elements input list:","code":"library(dplyr) library(purrr) library(stringr) ## Retaining only markers and genes on chromosomes 7 and 8 x_small <- x |> map(~ filter(.x, str_detect(chromosome, \"(07|08)\"))) ## Creating a second GWAS result tibble by shuffling ## the marker scores from the original data gwas_1 <- x_small[[\"GWAS\"]] gwas_2 <- gwas_1 |> mutate(score = sample(score)) hidecan_plot( gwas_list = list(gwas_1, gwas_2), score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0 ) hidecan_plot( gwas_list = list(\"Trait 1\" = gwas_1, \"Trait 2\" = gwas_2), score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0 )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"defining-chromosomes-length","dir":"Articles","previous_headings":"","what":"Defining chromosomes length","title":"hidecan","text":"default, hidecan_plot() function calculates length different chromosomes based input data, looking maximum position genes markers chromosome. However, also possible pass tibble chromosome length (bp) chrom_length argument. Note case can’t really see difference computed chromosome length values.","code":"library(tibble) ## Chromosomes length as recorded in Ensembl Plants potato_chrom_length <- c( ST4.03ch00 = 45813526, ST4.03ch01 = 88663952, ST4.03ch02 = 48614681, ST4.03ch03 = 62190286, ST4.03ch04 = 72208621, ST4.03ch05 = 52070158, ST4.03ch06 = 59532096, ST4.03ch07 = 56760843, ST4.03ch08 = 56938457, ST4.03ch09 = 61540751, ST4.03ch10 = 59756223, ST4.03ch11 = 45475667, ST4.03ch12 = 61165649 ) |> ## turn a named vector into a tibble enframe(name = \"chromosome\", value = \"length\") head(potato_chrom_length) #> # A tibble: 6 × 2 #> chromosome length #> #> 1 ST4.03ch00 45813526 #> 2 ST4.03ch01 88663952 #> 3 ST4.03ch02 48614681 #> 4 ST4.03ch03 62190286 #> 5 ST4.03ch04 72208621 #> 6 ST4.03ch05 52070158 hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, chrom_length = potato_chrom_length )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"controlling-the-plot-properties","dir":"Articles","previous_headings":"","what":"Controlling the plot properties","title":"hidecan","text":"hidecan_plot() function offers several arguments control different aspects HIDECAN plot. example, possible specify number rows columns plot , n_rows n_cols arguments. Note one arguments considered (n_rows takes precedence): addition, possible : add title subtitle plot (title subtitle arguments); control position legend (legend_position argument); control size points (point_size argument); control size labels padding around text candidate genes labels (label_size label_padding arguments).","code":"## Specifying the number of rows hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, n_rows = 3 ) ## Specifying the number of columns hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.005), log2fc_thr = 0, n_cols = 3 )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"creating-a-manhattan-plot","dir":"Articles","previous_headings":"","what":"Creating a Manhattan plot","title":"hidecan","text":"possible visualise GWAS results Manhattan plot manhattan_plot() function. function takes input data-frame (list data-frames) GWAS results, must follow rules plot_hidecan() function (see section vignette). horizontal line representing significance threshold can added plot, passing threshold value score_thr argument. hidecan_plot() function, possible pass list GWAS results function, order draw several Manhattan plots one figure. names list used identify different plots:","code":"manhattan_plot(x[[\"GWAS\"]], score_thr = 4) manhattan_plot(list(\"Trait A\" = x[[\"GWAS\"]], \"Trait B\" = x[[\"GWAS\"]]), score_thr = 4, ncol = 1)"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"controlling-the-aesthetics-colours-point-shapes-labels-of-the-tracks","dir":"Articles","previous_headings":"","what":"Controlling the aesthetics (colours, point shapes, labels) of the tracks","title":"hidecan","text":"default look different data types (GWAS peaks, DE genes candidate genes) HIDECAN plots controlled arguments returned hidecan_aes(). specifically, function controls: label data type x-axis (e.g. ‘GWAS peaks’ GWAS results), colour vertical lines used showcase position markers genes, shape points, whether name markers/genes displayed (default, show candidate genes), colour palette used score log2 fold-change points. default values used parameters chosen ensure resulting plot easily understandable. However, possible change . , ’ll start saving defaults returned hidecan_aes(): can see , function returns list default aesthetics use GWAS results (GWAS_data_thr element), DE results (DE_data_thr element), candidate genes (CAN_data_thr element), custom tracks (CUSTOM_data_thr element - see Adding custom tracks article information). element list, containing value attribute mentioned . Let’s modify label given GWAS peaks, colour palette used DE score: can use modified values passing list hidecan_plot() custom_aes argument:","code":"default_aes <- hidecan_aes() str(default_aes, max.level = 1) #> List of 4 #> $ GWAS_data_thr :List of 5 #> $ DE_data_thr :List of 5 #> $ CAN_data_thr :List of 5 #> $ CUSTOM_data_thr:List of 5 default_aes[[1]] #> $y_label #> [1] \"GWAS peaks\" #> #> $line_colour #> [1] \"red\" #> #> $point_shape #> [1] 21 #> #> $show_name #> [1] FALSE #> #> $fill_scale #> #> Range: #> Limits: 0 -- 1 library(viridis) default_aes$GWAS_data_thr$y_label <- \"GWAS signif. markers\" default_aes$DE_data_thr$fill_scale <- scale_fill_viridis( \"DE gene score\", option = \"inferno\", guide = ggplot2::guide_colourbar( title.position = \"top\", title.hjust = 0.5, order = 3 # ensures this legend is shown after the one for GWAS scores ) ) hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, custom_aes = default_aes )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html","id":"viewport-error","dir":"Articles","previous_headings":"","what":"Viewport error","title":"hidecan","text":"working RStudio, may encounter following error: caused plotting window small. Try increasing size plotting window RStudio console. Alternatively, can save plot R object, use ggplot2::ggsave() save file:","code":"#> Error in grid.Call(C_convert, x, as.integer(whatfrom), as.integer(whatto), : Viewport has zero dimension(s) p <- hidecan_plot( gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, label_size = 2 ) ggplot2::ggsave(\"hidecan_plot.pdf\", p, width = 10, height = 10)"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/web_only/custom_tracks.html","id":"adding-one-custom-data-type","dir":"Articles > Web_only","previous_headings":"","what":"Adding one custom data type","title":"Adding custom tracks","text":"Let us start simulating new set results – simplicity ’ll assume results QTL mapping markers used GWAS analysis: can add new data hidecan plot custom_list argument hidecan_plot() function (’ll look two chromosomes simplicity), use score_thr_custom argument set significance threshold score: Importantly, data-frame passed custom_list must contain least following columns: chromosome, position score. genomic features want add genes example (start end position) need calculate position column . can customise labels colours used custom track help hidecan_aes() function: particular, change name given track, well name used legend: use values hidecan plot passing list custom_aes argument: Note , supported data types, can pass one data-frame custom_list get several tracks QTLs: default, values score column shown points colour, can hide setting fill_scale element aesthetics list NULL. Also, can add labels significant points, adding name column data-frame, setting show_name element aesthetics list TRUE:","code":"x <- get_example_data() set.seed(586) x$QTL <- x$GWAS |> ## shuffling the scores around to get different \"significant\" markers mutate(score = sample(score, n(), replace = FALSE)) hidecan_plot( gwas_list = x[[\"GWAS\"]], score_thr_gwas = -log10(0.0001), chroms = c(\"ST4.03ch01\", \"ST4.03ch02\"), custom_list = x[[\"QTL\"]], score_thr_custom = -log10(0.0001) ) plot_aes <- hidecan_aes() str(plot_aes, max.level = 1) #> List of 4 #> $ GWAS_data_thr :List of 5 #> $ DE_data_thr :List of 5 #> $ CAN_data_thr :List of 5 #> $ CUSTOM_data_thr:List of 5 plot_aes[[\"CUSTOM_data_thr\"]] #> $y_label #> [1] \"Custom track\" #> #> $line_colour #> [1] \"darkgoldenrod2\" #> #> $point_shape #> [1] 21 #> #> $show_name #> [1] FALSE #> #> $fill_scale #> #> Range: #> Limits: 0 -- 1 plot_aes$CUSTOM_data_thr$y_label <- \"Signif. QTLs\" plot_aes$CUSTOM_data_thr$fill_scale$name <- \"QTL score\" # We could also change the entire legend with: # default_aes$CUSTOM_data_thr$fill_scale <- scale_fill_viridis( # \"QTL score\", # option = \"inferno\", # guide = guide_colourbar( # title.position = \"top\", # title.hjust = 0.5, # order = 4 # ensures this legend is shown after the one for DE scores # ) # ) hidecan_plot( gwas_list = x[[\"GWAS\"]], score_thr_gwas = -log10(0.0001), chroms = c(\"ST4.03ch01\", \"ST4.03ch02\"), custom_list = x[[\"QTL\"]], score_thr_custom = -log10(0.0001), custom_aes = plot_aes ) ## Simulating a second set of QTL results set.seed(779) x$QTL2 <- x$QTL |> mutate(score = sample(score, n(), replace = FALSE)) hidecan_plot( gwas_list = x[[\"GWAS\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.05), log2fc_thr = 0, chroms = c(\"ST4.03ch01\", \"ST4.03ch02\"), custom_list = list(\"Trait 1\" = x[[\"QTL\"]], \"Trait 2\" = x[[\"QTL2\"]]), score_thr_custom = -log10(0.0001), custom_aes = plot_aes ) ## Creating fake names for the markers set.seed(342) x$QTL <- x$QTL |> mutate(name = sample(LETTERS, n(), replace = TRUE)) plot_aes2 <- plot_aes plot_aes2$CUSTOM_data_thr$show_name <- TRUE plot_aes2$CUSTOM_data_thr$fill_scale <- NULL hidecan_plot( gwas_list = x[[\"GWAS\"]], score_thr_gwas = -log10(0.0001), chroms = c(\"ST4.03ch01\", \"ST4.03ch02\"), custom_list = x[[\"QTL\"]], score_thr_custom = -log10(0.0001), custom_aes = plot_aes2 )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/web_only/custom_tracks.html","id":"adding-several-custom-data-types","dir":"Articles > Web_only","previous_headings":"","what":"Adding several custom data types","title":"Adding custom tracks","text":"also possible add one custom data type. example, let’s say want add information differentially methylated regions plot. ’ll use example DE data simulate methylated dataset: Importantly, significance threshold encoded score_thr_custom argument hidecan_plot() used custom datasets, don’t want use significance threshold QTL methylation data, need perform filtering significant features hand set threshold 0: key specifying two custom datasets different data types add new data-frame argument called aes_type, simply label tells function aesthetics settings use list passsed custom_aes. retain aesthetics set QTL scores, create new aesthetics methylation data: restrictions number custom data types can added hidecan plot.","code":"set.seed(554) x$METH <- x$DE |> mutate( position = (start + end) / 2, ## need to calculate the position of the regions score = sample(-log10(padj), n(), replace = FALSE), name = sample(letters, n(), replace = TRUE) ) x$QTL <- x$QTL |> filter(score >= -log10(0.0001)) x$METH <- x$METH |> filter(score >= -log10(0.04)) ## Adding the aes_type attribute to the methylation data attr(x$METH, \"aes_type\") <- \"METH\" ## The name of the new element in the aesthetics list must match the value of ## the aes_type attribute plot_aes$METH <- list( y_label = \"DMRs\", line_colour = \"purple\", point_shape = 24, show_name = TRUE, fill_scale = scale_fill_viridis( \"DM score\", option = \"mako\", guide = guide_colourbar( title.position = \"top\", title.hjust = 0.5, order = 5 ) ) ) hidecan_plot( gwas_list = x[[\"GWAS\"]], score_thr_gwas = -log10(0.0001), chroms = c(\"ST4.03ch01\", \"ST4.03ch02\"), custom_list = list(x[[\"QTL\"]], x[[\"METH\"]]), score_thr_custom = 0, ## no filtering, has been done manually custom_aes = plot_aes )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/web_only/gwaspoly_output.html","id":"gwaspoly-example-data","dir":"Articles > Web_only","previous_headings":"","what":"GWASpoly example data","title":"HIDECAN plot from GWASpoly output","text":"example GWASpoly output, based original example dataset GWASpoly package provided package can loaded 1: example, three traits analysed: tuber_eye_depth, tuber_shape sucrose. trait, GWAS scores computed four different genetic models: general, additive, 1-dom-alt 1-dom-ref: See Appendix section bottom vignette code used generate example data.","code":"gwaspoly_res_thr <- readRDS(system.file(\"extdata/gwaspoly_res_thr.rda\", package = \"hidecan\")) ## Traits analysed names(gwaspoly_res_thr@scores) #> [1] \"tuber_eye_depth\" \"tuber_shape\" \"sucrose\" ## Genetic models tests head(gwaspoly_res_thr@scores[[1]]) #> general additive 1-dom-alt 1-dom-ref #> c2_41437 0.45584445 0.4774282 0.1430731 NA #> c2_24258 0.32552500 0.1655215 NA 0.0431065 #> c2_21332 0.06251865 0.2263273 0.1562208 0.4488712 #> c2_21320 0.92927679 0.5774697 NA 1.0170807 #> c2_21318 0.09043940 0.2200563 0.1410284 NA #> c2_21314 0.19480464 0.6442068 NA 0.4286548"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/web_only/gwaspoly_output.html","id":"hidecan-plot-from-gwaspoly-output","dir":"Articles > Web_only","previous_headings":"","what":"HIDECAN plot from GWASpoly output","title":"HIDECAN plot from GWASpoly output","text":"hidecan_plot_from_gwaspoly() function reads GWASpoly.thresh object, extracts marker scores combination trait genetic model, uses construct HIDECAN plot. y-axis, trait indicated first, genetic model next brackets: HIDECAN plot, can easily see genomic region around 50Mb chromosome 10 significantly associated tuber eye depth shape, using either general additive model. region significantly associated either traits considering one simplex dominant models. sucrose phenotype, general model detected significant markers. possible specify traits /genetic models represented HIDECAN plot, via traits models arguments:","code":"hidecan_plot_from_gwaspoly( gwaspoly_res_thr, remove_empty_chrom = TRUE ) hidecan_plot_from_gwaspoly( gwaspoly_res_thr, traits = c(\"tuber_eye_depth\", \"tuber_shape\"), models = \"general\", remove_empty_chrom = TRUE )"},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/web_only/gwaspoly_output.html","id":"the-gwaspoly-constructor","dir":"Articles > Web_only","previous_headings":"","what":"The GWASpoly constructor","title":"HIDECAN plot from GWASpoly output","text":"hood, hidecan_plot_from_gwaspoly() function relies GWAS_data_from_gwaspoly() constructor, takes input either: GWASpoly.fitted object (returned GWASpoly::GWASpoly() function), GWASpoly.thresh object (returned GWASpoly::set.threshold() function). function extracts marker scores traits genetic models present GWASpoly output, well length chromosomes. addition, input data GWASpoly.thresh object, extracts significance threshold combination trait genetic model, uses filter significant markers.","code":"gwaspoly_data <- GWAS_data_from_gwaspoly(gwaspoly_res_thr) ## GWAS_data objects, i.e. tibbles of marker scores str(gwaspoly_data$gwas_data_list, max.level = 1) #> List of 12 #> $ tuber_eye_depth (general) : GWAS_dat [3,507 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ tuber_eye_depth (additive) : GWAS_dat [3,507 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ tuber_eye_depth (1-dom-alt): GWAS_dat [2,054 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ tuber_eye_depth (1-dom-ref): GWAS_dat [2,174 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ tuber_shape (general) : GWAS_dat [3,507 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ tuber_shape (additive) : GWAS_dat [3,507 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ tuber_shape (1-dom-alt) : GWAS_dat [2,054 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ tuber_shape (1-dom-ref) : GWAS_dat [2,174 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ sucrose (general) : GWAS_dat [3,506 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ sucrose (additive) : GWAS_dat [3,507 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ sucrose (1-dom-alt) : GWAS_dat [2,054 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) #> $ sucrose (1-dom-ref) : GWAS_dat [2,174 × 4] (S3: GWAS_data/tbl_df/tbl/data.frame) ## GWAS_data_thr objects, i.e. tibbles of significant markers str(gwaspoly_data$gwas_data_thr_list, max.level = 1) #> List of 12 #> $ tuber_eye_depth (general) : GWAS_dt_ [1 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ tuber_eye_depth (additive) : GWAS_dt_ [3 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ tuber_eye_depth (1-dom-alt): GWAS_dt_ [0 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ tuber_eye_depth (1-dom-ref): GWAS_dt_ [0 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ tuber_shape (general) : GWAS_dt_ [2 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ tuber_shape (additive) : GWAS_dt_ [2 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ tuber_shape (1-dom-alt) : GWAS_dt_ [0 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ tuber_shape (1-dom-ref) : GWAS_dt_ [0 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ sucrose (general) : GWAS_dt_ [2 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ sucrose (additive) : GWAS_dt_ [0 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ sucrose (1-dom-alt) : GWAS_dt_ [0 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) #> $ sucrose (1-dom-ref) : GWAS_dt_ [0 × 4] (S3: GWAS_data_thr/tbl_df/tbl/data.frame) ## Chromosomes length str(gwaspoly_data$chrom_length) #> tibble [13 × 2] (S3: tbl_df/tbl/data.frame) #> $ chromosome: Ord.factor w/ 13 levels \"0\"<\"1\"<\"2\"<\"3\"<..: 1 2 3 4 5 6 7 8 9 10 ... #> $ length : int [1:13] 36454137 88583876 48564909 61870684 72026885 51998374 59263222 56628128 56785385 61466245 ..."},{"path":"https://plantandfoodresearch.github.io/hidecan/articles/web_only/gwaspoly_output.html","id":"appendix-reproducing-the-gwaspoly-example-data","dir":"Articles > Web_only","previous_headings":"","what":"Appendix: reproducing the GWASpoly example data","title":"HIDECAN plot from GWASpoly output","text":"example dataset provided can reproduced following code:","code":"library(GWASpoly) genofile <- system.file(\"extdata\", \"TableS1.csv\", package = \"GWASpoly\") phenofile <- system.file(\"extdata\", \"TableS2.csv\", package = \"GWASpoly\") ## Reading example data data <- read.GWASpoly( ploidy = 4, pheno.file = phenofile, geno.file = genofile, format = \"ACGT\", n.traits = 13, delim = \",\" ) ## Computing K matrix data.original <- set.K( data, LOCO = FALSE, n.core = 2 ) ## Performing GWAS gwaspoly_res <- GWASpoly( data.original, models = c(\"general\", \"additive\", \"1-dom\"), traits = c(\"tuber_eye_depth\", \"tuber_shape\", \"sucrose\"), n.core = 2 ) ## Computing significance threshold ## Object returned by get_gwaspoly_example_data() gwaspoly_res_thr <- set.threshold( gwaspoly_res, method = \"M.eff\", level = 0.05 ) # saveRDS(gwaspoly_res_thr, \"gwaspoly_res_thr.rda)"},{"path":"https://plantandfoodresearch.github.io/hidecan/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Olivia Angelin-Bonnet. Author, maintainer.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Angelin-Bonnet O (2024). hidecan: Create HIDECAN Plots Visualising Genome-Wide Association Studies Differential Expression Results. R package version 1.1.0.9000, https://github.com/PlantandFoodResearch/hidecan, https://plantandfoodresearch.github.io/hidecan/.","code":"@Manual{, title = {hidecan: Create HIDECAN Plots for Visualising Genome-Wide Association Studies and Differential Expression Results}, author = {Olivia Angelin-Bonnet}, year = {2024}, note = {R package version 1.1.0.9000, https://github.com/PlantandFoodResearch/hidecan}, url = {https://plantandfoodresearch.github.io/hidecan/}, }"},{"path":"https://plantandfoodresearch.github.io/hidecan/index.html","id":"hidecan-","dir":"","previous_headings":"","what":"Create HIDECAN Plots for Visualising Genome-Wide Association Studies and Differential Expression Results","title":"Create HIDECAN Plots for Visualising Genome-Wide Association Studies and Differential Expression Results","text":"hidecan R package generating HIDECAN plots, visualisations summarising results one Genome-wide association study (GWAS) transcriptomics differential expression (DE) analysis, alongside candidate genes interest.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Create HIDECAN Plots for Visualising Genome-Wide Association Studies and Differential Expression Results","text":"hidecan available CRAN can installed via: Alternatively, can install development version hidecan GitHub :","code":"install.packages(\"hidecan\") # install.packages(\"devtools\") devtools::install_github(\"PlantandFoodResearch/hidecan\")"},{"path":"https://plantandfoodresearch.github.io/hidecan/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"Create HIDECAN Plots for Visualising Genome-Wide Association Studies and Differential Expression Results","text":"hidecan package works follows: takes input one data-frames containing GWAS results, differential expression results list candidate genes interest; computes length chromosome based genomic position markers genes provided input data; filters datasets retain significant markers differentially expressed genes, according threshold score /log2-fold change. fold-change set user, can different GWAS differential expression results. displays position significant markers genes alongside candidate genes (HIDECAN plot). plot can customised user via number parameters (e.g. legend position label size). wrapper function hidecan_plot() performs steps. use demonstrated example dataset:","code":"library(hidecan) ## Getting an example dataset x <- get_example_data() hidecan_plot( gwas_list = x[[\"GWAS\"]], ## data-frame of GWAS results de_list = x[[\"DE\"]], ## data-frame of DE results can_list = x[[\"CAN\"]], ## data-frame of candidate genes score_thr_gwas = -log10(0.0001), ## sign. threshold for GWAS score_thr_de = -log10(0.05), ## sign. threshold for DE log2fc_thr = 0, ## log2FC threshold for DE label_size = 2 ## label size for candidate genes )"},{"path":"https://plantandfoodresearch.github.io/hidecan/index.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Create HIDECAN Plots for Visualising Genome-Wide Association Studies and Differential Expression Results","text":"using HIDECAN, please cite: Angelin-Bonnet, O., Vignes, M., Biggs, P. J., Baldwin, S., & Thomson, S. (2023). Visual integration GWAS differential expression results hidecan R package. bioRxiv, 2023-03. https://doi.org/10.1101/2023.03.30.535015","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CAN_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a CAN_data object — CAN_data","title":"Creates a CAN_data object — CAN_data","text":"Creates CAN_data object tibble data-frame candidate genes.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CAN_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a CAN_data object — CAN_data","text":"","code":"CAN_data(dat, keep_rownames_as = NULL)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CAN_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a CAN_data object — CAN_data","text":"dat Tibble, set candidate genes interest. See Details. keep_rownames_as Character, name column save rownames input data-frame. Default value NULL, .e. rownames discarded.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CAN_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a CAN_data object — CAN_data","text":"CAN_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CAN_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Creates a CAN_data object — CAN_data","text":"input data one row per gene, least following columns: chromosome: character column, chromosome gene located. start end: numeric, starting end position gene (bp). column position constructed middle value (mean) start end. name: character, name candidate genes displayed.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CAN_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a CAN_data object — CAN_data","text":"","code":"x <- get_example_data() CAN_data(x[[\"CAN\"]]) #> # A tibble: 32 × 7 #> id chromosome start end name gene_name position #> #> 1 PGSC0003DMG400003155 ST4.03ch03 46757152 46762127 4CL 4-coumar… 4.68e7 #> 2 PGSC0003DMG400014223 ST4.03ch03 57466692 57469946 4CL2 4-coumar… 5.75e7 #> 3 PGSC0003DMG400011189 ST4.03ch07 1001854 1006278 HQT HQT 1.00e6 #> 4 PGSC0003DMG400005492 ST4.03ch05 36342746 36347409 PAL phenylal… 3.63e7 #> 5 PGSC0003DMG400005279 ST4.03ch05 42523943 42525912 peroxi… peroxida… 4.25e7 #> 6 PGSC0003DMG400007782 ST4.03ch03 38537202 38540209 PHO1A PHO1A 3.85e7 #> 7 PGSC0003DMG400023182 ST4.03ch02 10091564 10093164 LIPIII… LipIII27 1.01e7 #> 8 PGSC0003DMG400029576  ST4.03ch08 45676042 45677832 PPOs Polyphen… 4.57e7 #> 9 PGSC0003DMG400018924 ST4.03ch08 45778567 45780333 NA Polyphen… 4.58e7 #> 10 PGSC0003DMG400018919 ST4.03ch08 45793661 45794229 NA Polyphen… 4.58e7 #> # ℹ 22 more rows"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CUSTOM_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a CUSTOM_data object — CUSTOM_data","title":"Creates a CUSTOM_data object — CUSTOM_data","text":"Creates CUSTOM_data object tibble data-frame custom genomic features.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CUSTOM_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a CUSTOM_data object — CUSTOM_data","text":"","code":"CUSTOM_data(dat, keep_rownames_as = NULL)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CUSTOM_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a CUSTOM_data object — CUSTOM_data","text":"dat Tibble custom genomic features. See Details. keep_rownames_as Character, name column save rownames input data-frame. Default value NULL, .e. rownames discarded.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CUSTOM_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a CUSTOM_data object — CUSTOM_data","text":"CUSTOM_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CUSTOM_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Creates a CUSTOM_data object — CUSTOM_data","text":"input data one row per marker, least following columns: chromosome: character column, chromosome feature located. position: numeric, physical position feature along chromosome (bp). score: numeric, score used genomic feature.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/CUSTOM_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a CUSTOM_data object — CUSTOM_data","text":"","code":"x <- get_example_data() CUSTOM_data(x[[\"GWAS\"]]) #> # A tibble: 35,481 × 4 #> id chromosome position score #> #> 1 ST4.03ch00_45467783 ST4.03ch00 45467783 0.191 #> 2 ST4.03ch01_88589716 ST4.03ch01 88589716 1.84 #> 3 ST4.03ch02_48614228 ST4.03ch02 48614228 0.381 #> 4 ST4.03ch03_62263578 ST4.03ch03 62263578 0.661 #> 5 ST4.03ch04_72139135 ST4.03ch04 72139135 0.640 #> 6 ST4.03ch05_52040302 ST4.03ch05 52040302 0.346 #> 7 ST4.03ch06_59434834 ST4.03ch06 59434834 1.13 #> 8 ST4.03ch07_56713057 ST4.03ch07 56713057 0.213 #> 9 ST4.03ch08_56937627 ST4.03ch08 56937627 0.843 #> 10 ST4.03ch09_61537423 ST4.03ch09 61537423 0.512 #> # ℹ 35,471 more rows"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/DE_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a DE_data object — DE_data","title":"Creates a DE_data object — DE_data","text":"Creates DE_data object tibble data-frame differential expression results.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/DE_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a DE_data object — DE_data","text":"","code":"DE_data(dat, keep_rownames_as = NULL)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/DE_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a DE_data object — DE_data","text":"dat Tibble, results differential expression analysis. See Details. keep_rownames_as Character, name column save rownames input data-frame. Default value NULL, .e. rownames discarded.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/DE_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a DE_data object — DE_data","text":"DE_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/DE_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Creates a DE_data object — DE_data","text":"input data one row per gene transcript, least following columns: chromosome: character column, chromosome gene/transcript located. start end: numeric, starting end position gene/transcript (bp). column position constructed middle value (mean) start end. score padj: numeric, DE score adjusted p-value gene/transcript. column score column missing, constructed -log10(padj). foldChange log2FoldChange: numeric, fold-change log2(fold-change) gene/transcript. column log2FoldChange missing, constructed log2(foldChange).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/DE_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a DE_data object — DE_data","text":"","code":"x <- get_example_data() DE_data(x[[\"DE\"]]) #> # A tibble: 10,671 × 9 #> gene chromosome padj log2FoldChange start end label score position #> #> 1 PGSC00… ST4.03ch00 0.787 0.0114 4.58e7 4.58e7 Prot… 0.104 4.58e7 #> 2 PGSC00… ST4.03ch01 0.630 0.00529 8.86e7 8.86e7 PhD-… 0.201 8.86e7 #> 3 PGSC00… ST4.03ch02 0.864 0.00362 4.86e7 4.86e7 Acet… 0.0637 4.86e7 #> 4 PGSC00… ST4.03ch03 0.530 0.0320 6.23e7 6.23e7 Phos… 0.276 6.23e7 #> 5 PGSC00… ST4.03ch04 0.975 0.00225 7.22e7 7.22e7 Cons… 0.0109 7.22e7 #> 6 PGSC00… ST4.03ch05 NA -0.000726 5.20e7 5.20e7 Cons… NA 5.20e7 #> 7 PGSC00… ST4.03ch06 0.844 -0.00323 5.95e7 5.95e7 30S … 0.0739 5.95e7 #> 8 PGSC00… ST4.03ch07 0.944 -0.00337 5.67e7 5.67e7 Ent-… 0.0252 5.67e7 #> 9 PGSC00… ST4.03ch08 0.403 0.0290 5.68e7 5.68e7 B3 d… 0.394 5.68e7 #> 10 PGSC00… ST4.03ch09 NA -0.000241 6.15e7 6.15e7 Cons… NA 6.15e7 #> # ℹ 10,661 more rows"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a GWAS_data object — GWAS_data","title":"Creates a GWAS_data object — GWAS_data","text":"Creates GWAS_data object tibble data-frame GWAS results.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a GWAS_data object — GWAS_data","text":"","code":"GWAS_data(dat, keep_rownames_as = NULL)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a GWAS_data object — GWAS_data","text":"dat Tibble, results GWAS analysis. See Details. keep_rownames_as Character, name column save rownames input data-frame. Default value NULL, .e. rownames discarded.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a GWAS_data object — GWAS_data","text":"GWAS_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Creates a GWAS_data object — GWAS_data","text":"input data one row per marker, least following columns: chromosome: character column, chromosome marker located. position: numeric, physical position marker along chromosome (bp). score padj: numeric, GWAS score adjusted p-value marker. column score column missing, constructed -log10(padj).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a GWAS_data object — GWAS_data","text":"","code":"x <- get_example_data() GWAS_data(x[[\"GWAS\"]]) #> # A tibble: 35,481 × 4 #> id chromosome position score #> #> 1 ST4.03ch00_45467783 ST4.03ch00 45467783 0.191 #> 2 ST4.03ch01_88589716 ST4.03ch01 88589716 1.84 #> 3 ST4.03ch02_48614228 ST4.03ch02 48614228 0.381 #> 4 ST4.03ch03_62263578 ST4.03ch03 62263578 0.661 #> 5 ST4.03ch04_72139135 ST4.03ch04 72139135 0.640 #> 6 ST4.03ch05_52040302 ST4.03ch05 52040302 0.346 #> 7 ST4.03ch06_59434834 ST4.03ch06 59434834 1.13 #> 8 ST4.03ch07_56713057 ST4.03ch07 56713057 0.213 #> 9 ST4.03ch08_56937627 ST4.03ch08 56937627 0.843 #> 10 ST4.03ch09_61537423 ST4.03ch09 61537423 0.512 #> # ℹ 35,471 more rows"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data_from_gwaspoly.html","id":null,"dir":"Reference","previous_headings":"","what":"Extracts information from GWASpoly output — GWAS_data_from_gwaspoly","title":"Extracts information from GWASpoly output — GWAS_data_from_gwaspoly","text":"Extracts GWAS results chromosome length GWASpoly output.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data_from_gwaspoly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extracts information from GWASpoly output — GWAS_data_from_gwaspoly","text":"","code":"GWAS_data_from_gwaspoly(gwaspoly_output, traits = NULL, models = NULL)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data_from_gwaspoly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extracts information from GWASpoly output — GWAS_data_from_gwaspoly","text":"gwaspoly_output GWASpoly.fitted GWASpoly.thresh object (returned GWASpoly::GWASpoly() GWASpoly::set.threshold() functions). traits Character vector, traits GWAS results extracted. NULL (default value), traits present considered. models Character vector, genetic models GWAS results extracted. NULL (default value), genetic models present considered.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data_from_gwaspoly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extracts information from GWASpoly output — GWAS_data_from_gwaspoly","text":"list following elements: gwas_data_list: named list GWAS_data objects, giving markers score possible trait/genetic model combination. names list form trait (genetic model). gwas_data_thr_list: input data GWASpoly.thresh object (GWASpoly::set.threshold() function), named list GwAS_data_thr, significant markers score possible trait/genetic model combination. names list form trait (genetic model). chrom_length: tibble one row per chromosome, giving length (bp) chromosome.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/apply_threshold.html","id":null,"dir":"Reference","previous_headings":"","what":"Filters GWAS or DE results based on a threshold — apply_threshold","title":"Filters GWAS or DE results based on a threshold — apply_threshold","text":"Filters markers genes/transcripts based threshold applied GWAS DE score, log2(fold-change) (applicable). set candidate genes, simply returns list. Note markers genes missing score log2(fold-change) removed dataset.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/apply_threshold.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filters GWAS or DE results based on a threshold — apply_threshold","text":"","code":"apply_threshold(x, score_thr = 0, log2fc_thr = 0) # S3 method for class 'GWAS_data' apply_threshold(x, score_thr = 0, log2fc_thr = 0) # S3 method for class 'DE_data' apply_threshold(x, score_thr = 0, log2fc_thr = 0) # S3 method for class 'CAN_data' apply_threshold(x, score_thr = 0, log2fc_thr = 0) # S3 method for class 'CUSTOM_data' apply_threshold(x, score_thr = 0, log2fc_thr = 0) # Default S3 method apply_threshold(x, score_thr = 0, log2fc_thr = 0)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/apply_threshold.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filters GWAS or DE results based on a threshold — apply_threshold","text":"x Either GWAS_data, DE_data, CAN_data CUSTOM_data object. score_thr Numeric, threshold use markers' genes/transcripts' score. markers genes score equal higher threshold retained. Default value 0. Ignored CAN_data. log2fc_thr Numeric, threshold use absolute value genes/ transcripts' log2(fold-change). genes/transcripts absolute log2(fold-change) equal higher threshold retained. Ignored GWAS_data, CAN_data CUSTOM_data.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/apply_threshold.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filters GWAS or DE results based on a threshold — apply_threshold","text":"filtered tibble (class GWAS_data_thr, DE_data_thr, CAN_data_thr CUSTOM_data_thr).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/apply_threshold.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Filters GWAS or DE results based on a threshold — apply_threshold","text":"","code":"x <- get_example_data() ## For GWAS results apply_threshold(GWAS_data(x[[\"GWAS\"]]), score_thr = 4) #> # A tibble: 37 × 4 #> id chromosome position score #> #> 1 ST4.03ch00_22680252 ST4.03ch00 22680252 4.41 #> 2 ST4.03ch01_6317643 ST4.03ch01 6317643 4.15 #> 3 ST4.03ch01_7671100 ST4.03ch01 7671100 4.43 #> 4 ST4.03ch01_8653747 ST4.03ch01 8653747 4.69 #> 5 ST4.03ch01_12842648 ST4.03ch01 12842648 6.85 #> 6 ST4.03ch01_13334335 ST4.03ch01 13334335 5.24 #> 7 ST4.03ch01_13544786 ST4.03ch01 13544786 4.00 #> 8 ST4.03ch01_42743974 ST4.03ch01 42743974 4.00 #> 9 ST4.03ch01_42949112 ST4.03ch01 42949112 4.18 #> 10 ST4.03ch01_52529264 ST4.03ch01 52529264 4.85 #> # ℹ 27 more rows ## For DE results - in second line, no threshold is applied ## on the log2(fold-change) apply_threshold(DE_data(x[[\"DE\"]]), score_thr = -log10(0.05), log2fc_thr = 1) #> # A tibble: 5 × 9 #> gene chromosome padj log2FoldChange start end label score position #> #> 1 PGSC0003D… ST4.03ch01 0.0488 1.61 8.15e7 8.15e7 Gene… 1.31 8.15e7 #> 2 PGSC0003D… ST4.03ch03 0.0488 1.14 3.49e7 3.49e7 Gene… 1.31 3.49e7 #> 3 PGSC0003D… ST4.03ch03 0.0184 3.06 5.99e7 5.99e7 Phos… 1.73 5.99e7 #> 4 PGSC0003D… ST4.03ch05 0.0414 1.10 3.47e6 3.47e6 Cons… 1.38 3.47e6 #> 5 PGSC0003D… ST4.03ch09 0.0328 1.51 5.40e7 5.40e7 Vici… 1.48 5.40e7 apply_threshold(DE_data(x[[\"DE\"]]), score_thr = -log10(0.05), log2fc_thr = 0) #> # A tibble: 57 × 9 #> gene chromosome padj log2FoldChange start end label score position #> #> 1 PGSC000… ST4.03ch00 0.0488 0.838 3.80e7 3.80e7 Pept… 1.31 3.80e7 #> 2 PGSC000… ST4.03ch01 0.0362 -0.181 5.83e7 5.83e7 Cons… 1.44 5.83e7 #> 3 PGSC000… ST4.03ch01 0.0488 1.61 8.15e7 8.15e7 Gene… 1.31 8.15e7 #> 4 PGSC000… ST4.03ch01 0.00465 0.438 8.45e7 8.45e7 Phi-2 2.33 8.45e7 #> 5 PGSC000… ST4.03ch02 0.0488 0.325 2.26e7 2.26e7 Cons… 1.31 2.26e7 #> 6 PGSC000… ST4.03ch02 0.0266 0.768 3.32e7 3.32e7 Leuc… 1.58 3.32e7 #> 7 PGSC000… ST4.03ch02 0.0488 0.381 4.14e7 4.14e7 Cons… 1.31 4.14e7 #> 8 PGSC000… ST4.03ch02 0.0314 0.663 4.23e7 4.23e7 Home… 1.50 4.23e7 #> 9 PGSC000… ST4.03ch03 0.0488 -0.804 5.33e5 5.41e5 SNF2… 1.31 5.37e5 #> 10 PGSC000… ST4.03ch03 0.0493 -0.345 9.26e6 9.26e6 Dihy… 1.31 9.26e6 #> # ℹ 47 more rows ## No effect on the Candidate genes apply_threshold(CAN_data(x[[\"CAN\"]])) #> # A tibble: 32 × 7 #> id chromosome start end name gene_name position #> #> 1 PGSC0003DMG400003155 ST4.03ch03 46757152 46762127 4CL 4-coumar… 4.68e7 #> 2 PGSC0003DMG400014223 ST4.03ch03 57466692 57469946 4CL2 4-coumar… 5.75e7 #> 3 PGSC0003DMG400011189 ST4.03ch07 1001854 1006278 HQT HQT 1.00e6 #> 4 PGSC0003DMG400005492 ST4.03ch05 36342746 36347409 PAL phenylal… 3.63e7 #> 5 PGSC0003DMG400005279 ST4.03ch05 42523943 42525912 peroxi… peroxida… 4.25e7 #> 6 PGSC0003DMG400007782 ST4.03ch03 38537202 38540209 PHO1A PHO1A 3.85e7 #> 7 PGSC0003DMG400023182 ST4.03ch02 10091564 10093164 LIPIII… LipIII27 1.01e7 #> 8 PGSC0003DMG400029576  ST4.03ch08 45676042 45677832 PPOs Polyphen… 4.57e7 #> 9 PGSC0003DMG400018924 ST4.03ch08 45778567 45780333 NA Polyphen… 4.58e7 #> 10 PGSC0003DMG400018919 ST4.03ch08 45793661 45794229 NA Polyphen… 4.58e7 #> # ℹ 22 more rows"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/combine_chrom_length.html","id":null,"dir":"Reference","previous_headings":"","what":"Computes chromosomes' length from list — combine_chrom_length","title":"Computes chromosomes' length from list — combine_chrom_length","text":"Computes length (bp) chromosome list GWAS DE results well candidate gene lists.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/combine_chrom_length.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Computes chromosomes' length from list — combine_chrom_length","text":"","code":"combine_chrom_length(x)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/combine_chrom_length.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Computes chromosomes' length from list — combine_chrom_length","text":"x list GWAS_data, DE_data, CAN_data CUSTOM_data objects.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/combine_chrom_length.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Computes chromosomes' length from list — combine_chrom_length","text":"tibble two columns: chromosome (chromosome name) length (chromosome length base pair).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/combine_chrom_length.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Computes chromosomes' length from list — combine_chrom_length","text":"","code":"x <- get_example_data() y <- list(\"GWAS\" = GWAS_data(x[[\"GWAS\"]]), \"DE\" = DE_data(x[[\"DE\"]]), \"CAN\" = CAN_data(x[[\"CAN\"]])) combine_chrom_length(y) #> # A tibble: 13 × 2 #> chromosome length #> #> 1 ST4.03ch00 45813526 #> 2 ST4.03ch01 88627702 #> 3 ST4.03ch02 48614228 #> 4 ST4.03ch03 62263578 #> 5 ST4.03ch04 72170119 #> 6 ST4.03ch05 52040326 #> 7 ST4.03ch06 59476545 #> 8 ST4.03ch07 56715111 #> 9 ST4.03ch08 56937627 #> 10 ST4.03ch09 61539681 #> 11 ST4.03ch10 59687482 #> 12 ST4.03ch11 45409456 #> 13 ST4.03ch12 61152223"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/compute_chrom_length.html","id":null,"dir":"Reference","previous_headings":"","what":"Computes chromosomes' length — compute_chrom_length","title":"Computes chromosomes' length — compute_chrom_length","text":"Computes length (bp) chromosome maximum position markers genes chromosome.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/compute_chrom_length.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Computes chromosomes' length — compute_chrom_length","text":"","code":"compute_chrom_length(x) # S3 method for class 'GWAS_data' compute_chrom_length(x) # S3 method for class 'DE_data' compute_chrom_length(x) # S3 method for class 'CAN_data' compute_chrom_length(x) # S3 method for class 'CUSTOM_data' compute_chrom_length(x)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/compute_chrom_length.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Computes chromosomes' length — compute_chrom_length","text":"x Either GWAS_data, DE_data, CAN_data CUSTOM_data object.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/compute_chrom_length.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Computes chromosomes' length — compute_chrom_length","text":"tibble two columns: chromosome (chromosome name) length (chromosome length base pair).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/compute_chrom_length.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Computes chromosomes' length — compute_chrom_length","text":"","code":"x <- get_example_data() compute_chrom_length(GWAS_data(x[[\"GWAS\"]])) #> # A tibble: 13 × 2 #> chromosome length #> #> 1 ST4.03ch00 45467783 #> 2 ST4.03ch01 88589716 #> 3 ST4.03ch02 48614228 #> 4 ST4.03ch03 62263578 #> 5 ST4.03ch04 72139135 #> 6 ST4.03ch05 52040302 #> 7 ST4.03ch06 59434834 #> 8 ST4.03ch07 56713057 #> 9 ST4.03ch08 56937627 #> 10 ST4.03ch09 61537423 #> 11 ST4.03ch10 59687482 #> 12 ST4.03ch11 45409344 #> 13 ST4.03ch12 61148638 compute_chrom_length(DE_data(x[[\"DE\"]])) #> # A tibble: 13 × 2 #> chromosome length #> #> 1 ST4.03ch00 45813526 #> 2 ST4.03ch01 88627702 #> 3 ST4.03ch02 48578978 #> 4 ST4.03ch03 62258929 #> 5 ST4.03ch04 72170119 #> 6 ST4.03ch05 52040326 #> 7 ST4.03ch06 59476545 #> 8 ST4.03ch07 56715111 #> 9 ST4.03ch08 56849780 #> 10 ST4.03ch09 61539681 #> 11 ST4.03ch10 59684952 #> 12 ST4.03ch11 45409456 #> 13 ST4.03ch12 61152223 compute_chrom_length(CAN_data(x[[\"CAN\"]])) #> # A tibble: 7 × 2 #> chromosome length #> #> 1 ST4.03ch02 44537572 #> 2 ST4.03ch03 57469946 #> 3 ST4.03ch04 63041935 #> 4 ST4.03ch05 42525912 #> 5 ST4.03ch07 51457407 #> 6 ST4.03ch08 45907390 #> 7 ST4.03ch12 55092326"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/create_hidecan_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a HIDECAN plot — create_hidecan_plot","title":"Creates a HIDECAN plot — create_hidecan_plot","text":"Creates HIDECAN plot list filtered GWAS DE results /candidate genes.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/create_hidecan_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a HIDECAN plot — create_hidecan_plot","text":"","code":"create_hidecan_plot( x, chrom_length, colour_genes_by_score = TRUE, remove_empty_chrom = FALSE, chroms = NULL, chrom_limits = NULL, title = NULL, subtitle = NULL, n_rows = NULL, n_cols = 2, legend_position = \"bottom\", point_size = 3, label_size = 3.5, label_padding = 0.15, custom_aes = NULL )"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/create_hidecan_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a HIDECAN plot — create_hidecan_plot","text":"x list GWAS_data_thr, DE_data_thr, CAN_data_thr /CUSTOM_data_thr produced apply_threshold() function. named, names appended y-axis labels (use ' ' empty name list). chrom_length Tibble columns chromosome length, giving chromosome length bp (see combine_chrom_length() function). colour_genes_by_score Logical, whether colour genes score (TRUE) log2(fold-change) (FALSE). Default value TRUE. remove_empty_chrom Logical, chromosomes significant markers/genes candidate genes removed plot? Default value FALSE. chroms Character vector, name chromosomes include plot. NULL (default value), chromosomes included. chrom_limits Integer vector length 2, named list elements integer vectors length 2. vector, gives lower upper limit chromosomes (bp) use plot. named list, names correspond chromosome names. Gives chromosome lower upper limits (bp) use plot. specified chromosomes. Default value NULL, .e. limits applied chromosomes (plotted entirety). title Character, title plot. Default value NULL (.e. title added plot). subtitle Character, subtitle plot. Default value NULL (.e. subtitle added plot). n_rows Integer, number rows chromosomes create plot. Default value NULL. n_cols Integer, number columns chromosomes create plot. Default value 2. set NULL n_rows NULL. legend_position Character, position legend plot. Can bottom (default value), top, right, left none. point_size Numeric, size points plot. Default value 3. label_size Numeric, size gene labels plot. Default value 3.5 (geom_label_repel). label_padding Numeric, amount padding around gene labels plot, unit number. Default value 0.15 (geom_label_repel). custom_aes Named list plot aesthetics custom data types. See hidecan_aes() information content element. Default NULL (needed CUSTOM_data_thr objects x customise aesthetics default data tracks).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/create_hidecan_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a HIDECAN plot — create_hidecan_plot","text":"ggplot.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/create_hidecan_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a HIDECAN plot — create_hidecan_plot","text":"","code":"if (interactive()) { x <- get_example_data() y <- list(\"GWAS\" = GWAS_data(x[[\"GWAS\"]]), \"DE\" = DE_data(x[[\"DE\"]]), \"CAN\" = CAN_data(x[[\"CAN\"]])) chrom_length <- combine_chrom_length(y) z <- list( apply_threshold(y[[\"GWAS\"]], score_thr = 4), apply_threshold(y[[\"DE\"]], score_thr = 1.3, log2fc_thr = 0.5), apply_threshold(y[[\"CAN\"]]) ) create_hidecan_plot(z, chrom_length, label_size = 2) ## Colour genes according to their fold-change create_hidecan_plot(z, chrom_length, colour_genes_by_score = FALSE, label_size = 2) ## Add names to the datasets create_hidecan_plot(setNames(z, c(\"Genomics\", \"RNAseq\", \"My list\")), chrom_length, colour_genes_by_score = FALSE, label_size = 2) ## Add names to some of the datasets only (e.g. not for GWAS results) create_hidecan_plot(setNames(z, c(\" \", \"RNAseq\", \"My list\")), chrom_length, colour_genes_by_score = FALSE, label_size = 2) ## Set limits on all chromosomes (to \"zoom in\" to the 10-20Mb region) create_hidecan_plot(z, chrom_length, label_size = 2, chrom_limits = c(10e6, 20e6)) ## Set limits on some chromosomes only create_hidecan_plot(z, chrom_length, label_size = 2, chrom_limits = list(\"ST4.03ch00\" = c(10e6, 20e6), \"ST4.03ch02\" = c(15e6, 25e6))) }"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-add_data_type.html","id":null,"dir":"Reference","previous_headings":"","what":"Add data type to HIDECAN plot — .add_data_type","title":"Add data type to HIDECAN plot — .add_data_type","text":"Add data type HIDECAN plot","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-add_data_type.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add data type to HIDECAN plot — .add_data_type","text":"","code":".add_data_type( p, toplot, i, paes, add_new_legend, point_size, label_size, label_padding )"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-add_data_type.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add data type to HIDECAN plot — .add_data_type","text":"p Current ggplot. toplot Tibble data plot. Character, data type add plot. paes Named list, aesthetics use data type (see hidecan_aes() information required values). add_new_legend Logical, whether current data type requires new legend fill. point_size Numeric, size points plot. label_size Numeric, size gene labels plot. label_padding Numeric, amount padding around gene labels plot, unit number.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-add_data_type.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add data type to HIDECAN plot — .add_data_type","text":"Ggplot p new data type added.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-check_chrom_limits.html","id":null,"dir":"Reference","previous_headings":"","what":"Check chromosome limits — .check_chrom_limits","title":"Check chromosome limits — .check_chrom_limits","text":"Check chromosome limits","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-check_chrom_limits.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check chromosome limits — .check_chrom_limits","text":"","code":".check_chrom_limits(chrom_limits, chrom_length, chroms)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-check_chrom_limits.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check chromosome limits — .check_chrom_limits","text":"chrom_limits Integer vector length 2, named list elements integer vectors length 2. vector, gives lower upper limit chromosomes (bp) use plot. named list, names correspond chromosome names. Gives chromosome lower upper limits (bp) use plot. specified chromosomes. Default value NULL, .e. limits applied chromosomes (plotted entirety). chrom_length Tibble chromosome length. chroms Character vector, name chromosomes include plot.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-check_chrom_limits.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check chromosome limits — .check_chrom_limits","text":"Tibble chromosome limits use plot.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-check_chroms.html","id":null,"dir":"Reference","previous_headings":"","what":"Check chromosomes to plot — .check_chroms","title":"Check chromosomes to plot — .check_chroms","text":"Check chromosomes plot","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-check_chroms.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check chromosomes to plot — .check_chroms","text":"","code":".check_chroms(toplot, chrom_length, chroms, remove_empty_chrom)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-check_chroms.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check chromosomes to plot — .check_chroms","text":"toplot Tibble, main data-frame plot. chrom_length Tibble chromosome length. chroms Character vector, name chromosomes include plot. NULL (default value), chromosomes included. remove_empty_chrom Logical, chromosomes significant markers/genes candidate genes removed plot? Default value FALSE.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-check_chroms.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check chromosomes to plot — .check_chroms","text":"Character vector chromosomes plot.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-check_cols.html","id":null,"dir":"Reference","previous_headings":"","what":"Checks whether some columns are present in a tibble — .check_cols","title":"Checks whether some columns are present in a tibble — .check_cols","text":"Checks whether columns present tibble","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-check_cols.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Checks whether some columns are present in a tibble — .check_cols","text":"","code":".check_cols(x, col_names, param_name = \"Input data-frame\")"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-check_cols.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Checks whether some columns are present in a tibble — .check_cols","text":"x Tibble col_names character vector column names param_name Character, name dataframe use error message.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-check_cols.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Checks whether some columns are present in a tibble — .check_cols","text":"invisible NULL","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-compute_chrom_length_genes.html","id":null,"dir":"Reference","previous_headings":"","what":"Computes chromosomes' length for a tibble of genes — .compute_chrom_length_genes","title":"Computes chromosomes' length for a tibble of genes — .compute_chrom_length_genes","text":"Computes length (bp) chromosome maximum position genes chromosome.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-compute_chrom_length_genes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Computes chromosomes' length for a tibble of genes — .compute_chrom_length_genes","text":"","code":".compute_chrom_length_genes(x)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-compute_chrom_length_genes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Computes chromosomes' length for a tibble of genes — .compute_chrom_length_genes","text":"x Either DE_data CAN_data object.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-compute_chrom_length_genes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Computes chromosomes' length for a tibble of genes — .compute_chrom_length_genes","text":"tibble two columns: chromosome (chromosome name) length (chromosome length base pair).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-compute_chrom_length_markers.html","id":null,"dir":"Reference","previous_headings":"","what":"Computes chromosomes' length for a tibble of markers — .compute_chrom_length_markers","title":"Computes chromosomes' length for a tibble of markers — .compute_chrom_length_markers","text":"Computes length (bp) chromosome maximum position chromosomes chromosome.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-compute_chrom_length_markers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Computes chromosomes' length for a tibble of markers — .compute_chrom_length_markers","text":"","code":".compute_chrom_length_markers(x)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-compute_chrom_length_markers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Computes chromosomes' length for a tibble of markers — .compute_chrom_length_markers","text":"x Either GWAS_data CUSTOM_data object.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-compute_chrom_length_markers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Computes chromosomes' length for a tibble of markers — .compute_chrom_length_markers","text":"tibble two columns: chromosome (chromosome name) length (chromosome length base pair).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-get_aes_type.html","id":null,"dir":"Reference","previous_headings":"","what":"Returns either ","title":"Returns either ","text":"Returns either \"aes_type\" attribute object class","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-get_aes_type.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Returns either ","text":"","code":".get_aes_type(x)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-get_aes_type.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Returns either ","text":"x GWAS_data_thr, DE_data_thr, CAN_data_thr CUSTOM_data_thr object.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-get_aes_type.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Returns either ","text":"Either \"aes_type\" attribute object class.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-get_plot_aes.html","id":null,"dir":"Reference","previous_headings":"","what":"Computes plot aesthetics — .get_plot_aes","title":"Computes plot aesthetics — .get_plot_aes","text":"Get list aesthetics data types plot.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-get_plot_aes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Computes plot aesthetics — .get_plot_aes","text":"","code":".get_plot_aes(aes_types, colour_genes_by_score, custom_aes)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-get_plot_aes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Computes plot aesthetics — .get_plot_aes","text":"aes_types Character vector data types (one per dataset plot), computed .get_aes_type(). colour_genes_by_score Logical, whether colour genes score (TRUE) log2(fold-change) (FALSE). custom_aes Named list plot aesthetics custom data types. See hidecan_aes() information content element.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/dot-get_plot_aes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Computes plot aesthetics — .get_plot_aes","text":"Named list plot aesthetics.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/get_example_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Example dataset — get_example_data","title":"Example dataset — get_example_data","text":"Returns list example datasets.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/get_example_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Example dataset — get_example_data","text":"","code":"get_example_data()"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/get_example_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Example dataset — get_example_data","text":"list following elements: GWAS: tibble GWAS results, columns id, chromosome, position score. DE: tibble differential expression results, columns gene, chromosome, padj, log2FoldChange, start, end label. CAN: tibble candidate genes, columns id, chromosome, start, end, name gene_name.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/get_example_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Example dataset — get_example_data","text":"dataset used example presented : Angelin-Bonnet et al., BMC Plant Biology (2023). study, tetraploid potato plants half-sibling breeding population used assess genetic components tuber bruising. Capture sequencing used obtain genomic information individuals, genome-wide association study (GWAS) performed 72,847 genomic biallelic variants obtained 158 plants bruising score measured. GWAS analysis carried GWASpoly package. addition, expression data obtained 25,163 transcribed genes, differential expression (DE) analysis carried 41 low- 33 high-bruising samples. Finally, literature search yielded list 42 candidate genes identified previous studies involved potato tuber bruising mechanisms. subset GWAS DE results, well list candidate genes literature, made available function. complete GWAS results table, half genomic variants GWAS score < 3.5 randomly selected consequently discarded, yielding dataset GWAS scores 35,481 variants. Similarly, half transcribed genes DE results table adjusted p-value > 0.05 randomly selected discarded, yielding dataset DE results 10,671 transcribed genes. filtering performed reduce size datasets (accordance CRAN policies), ensures significant markers genes retained datasets. Finally, candidate genes located chromosome 3 removed example dataset better clarity resulting HIDECAN plot, leaving 32 candidate genes.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_aes.html","id":null,"dir":"Reference","previous_headings":"","what":"Default aesthetics for HIDECAN plot — hidecan_aes","title":"Default aesthetics for HIDECAN plot — hidecan_aes","text":"Generates list default aesthetics used HIDECAN plots.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_aes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Default aesthetics for HIDECAN plot — hidecan_aes","text":"","code":"hidecan_aes(colour_genes_by_score = TRUE)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_aes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Default aesthetics for HIDECAN plot — hidecan_aes","text":"colour_genes_by_score Logical, whether colour genes score (TRUE) log2(fold-change) (FALSE). Default value TRUE.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_aes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Default aesthetics for HIDECAN plot — hidecan_aes","text":"named list, one element per type data (e.g. GWAS, DE, etc). element list following elements: y_label: prefix added name track y-axis plot. line_colour: colour vertical line used show position elements type. point_shape: shape used points type. show_name: whether label name value added points type. fill_scale: fill scale use points type.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Wrapper to create a HIDECAN plot — hidecan_plot","title":"Wrapper to create a HIDECAN plot — hidecan_plot","text":"Wrapper function create HIDECAN plot GWAS results, DE results candidate genes.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Wrapper to create a HIDECAN plot — hidecan_plot","text":"","code":"hidecan_plot( gwas_list = NULL, de_list = NULL, can_list = NULL, score_thr_gwas = 4, score_thr_de = 2, log2fc_thr = 1, chrom_length = NULL, colour_genes_by_score = TRUE, remove_empty_chrom = FALSE, chroms = NULL, chrom_limits = NULL, title = NULL, subtitle = NULL, n_rows = NULL, n_cols = 2, legend_position = \"bottom\", point_size = 3, label_size = 3.5, label_padding = 0.15, custom_aes = NULL, custom_list = NULL, score_thr_custom = 0 )"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Wrapper to create a HIDECAN plot — hidecan_plot","text":"gwas_list Data-frame list data-frames containing GWAS results, least chromosome, position either padj score columns. named list, names used plot. de_list Data-frame list data-frames containing DE results, least chromosome, start, end, log2FoldChange either padj score columns. named list, names used plot. can_list Data-frame list data-frames containing candidate genes, least chromosome, start, end name columns. named list, names used plot. score_thr_gwas Numeric, score threshold GWAS results used select markers plotted. Default value 4. score_thr_de Numeric, score threshold DE results used select markers plotted. Default value 2. log2fc_thr Numeric, log2(fold-change) threshold used select genes plotted. Default value 1. chrom_length Optional, tibble columns chromosome length, giving chromosome length bp. NULL (default), inferred GWAS, DE candidate gene data. colour_genes_by_score Logical, whether colour genes score (TRUE) log2(fold-change) (FALSE). Default value TRUE. remove_empty_chrom Logical, chromosomes significant markers/genes candidate genes removed plot? Default value FALSE. chroms Character vector, name chromosomes include plot. NULL (default value), chromosomes included. chrom_limits Integer vector length 2, named list elements integer vectors length 2. vector, gives lower upper limit chromosomes (bp) use plot. named list, names correspond chromosome names. Gives chromosome lower upper limits (bp) use plot. specified chromosomes. Default value NULL, .e. limits applied chromosomes (plotted entirety). title Character, title plot. Default value NULL (.e. title added plot). subtitle Character, subtitle plot. Default value NULL (.e. subtitle added plot). n_rows Integer, number rows chromosomes create plot. Default value NULL. n_cols Integer, number columns chromosomes create plot. Default value 2. set NULL n_rows NULL. legend_position Character, position legend plot. Can bottom (default value), top, right, left none. point_size Numeric, size points plot. Default value 3. label_size Numeric, size gene labels plot. Default value 3.5 (geom_label_repel). label_padding Numeric, amount padding around gene labels plot, unit number. Default value 0.15 (geom_label_repel). custom_aes Named list plot aesthetics custom data types. See hidecan_aes() information content element. Default NULL (needed CUSTOM_data_thr objects x customise aesthetics default data tracks). custom_list Data-frame list data-frames containing custom genomic features, least chromosome, position score columns. named list, names used plot. score_thr_custom Numeric, score threshold custom genomic features used select markers plotted. Default value 0.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Wrapper to create a HIDECAN plot — hidecan_plot","text":"ggplot.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Wrapper to create a HIDECAN plot — hidecan_plot","text":"","code":"if (interactive()) { x <- get_example_data() ## Typical example with one GWAs result table, one DE result table and ## one table of candidate genes hidecan_plot(gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.005), log2fc_thr = 0, label_size = 2) ## Example with two sets of GWAS results hidecan_plot(gwas_list = list(x[[\"GWAS\"]], x[[\"GWAS\"]]), score_thr_gwas = 4) ## Example with two sets of DE results, with names hidecan_plot(de_list = list(\"X vs Y\" = x[[\"DE\"]], \"X vs Z\" = x[[\"DE\"]]), score_thr_de = -log10(0.05), log2fc_thr = 0) ## Set limits on all chromosomes (to \"zoom in\" to the 10-20Mb region) hidecan_plot(gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.005), log2fc_thr = 0, label_size = 2, chrom_limits = c(10e6, 20e6)) ## Set limits on some chromosomes only hidecan_plot(gwas_list = x[[\"GWAS\"]], de_list = x[[\"DE\"]], can_list = x[[\"CAN\"]], score_thr_gwas = -log10(0.0001), score_thr_de = -log10(0.005), log2fc_thr = 0, label_size = 2, chrom_limits = list(\"ST4.03ch00\" = c(10e6, 20e6), \"ST4.03ch02\" = c(15e6, 25e6))) }"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot_from_gwaspoly.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a HIDECAN plot from GWASpoly output — hidecan_plot_from_gwaspoly","title":"Creates a HIDECAN plot from GWASpoly output — hidecan_plot_from_gwaspoly","text":"Creates HIDECAN plot GWAS results GWASpoly.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot_from_gwaspoly.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a HIDECAN plot from GWASpoly output — hidecan_plot_from_gwaspoly","text":"","code":"hidecan_plot_from_gwaspoly(gwaspoly_output, traits = NULL, models = NULL, ...)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot_from_gwaspoly.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a HIDECAN plot from GWASpoly output — hidecan_plot_from_gwaspoly","text":"gwaspoly_output GWASpoly.thresh object (returned GWASpoly::set.threshold() function). traits Character vector, traits GWAS results extracted. NULL (default value), traits present considered. models Character vector, genetic models GWAS results extracted. NULL (default value), genetic models present considered. ... arguments passed create_hidecan_plot() function.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot_from_gwaspoly.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a HIDECAN plot from GWASpoly output — hidecan_plot_from_gwaspoly","text":"ggplot.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/manhattan_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Creates a Manhattan plot — manhattan_plot","title":"Creates a Manhattan plot — manhattan_plot","text":"Creates Manhattan plot data-frame GWAS results.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/manhattan_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Creates a Manhattan plot — manhattan_plot","text":"","code":"manhattan_plot( gwas_list, score_thr = NULL, chroms = NULL, title = NULL, subtitle = NULL, size_range = c(1, 3), chrom_col = NULL, ncol = NULL )"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/manhattan_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Creates a Manhattan plot — manhattan_plot","text":"gwas_list Data-frame list data-frames containing GWAS results, least chromosome, position either padj score columns. named list, names used plot. score_thr Numeric, significance threshold GWAS score. value provided, represented Manhattan plot red dashed line. NULL (default value), significance threshold line drawn. chroms Character vector, name chromosomes include plot. NULL (default value), chromosomes included. title Character, title plot. Default value NULL (.e. title added plot). subtitle Character, subtitle plot. Default value NULL (.e. subtitle added plot). size_range Numeric vector length 2, minimum maximum point size plot. Points size proportional GWAS score. Default value c(1, 3). chrom_col Character vector colour names code, colours use draw points chromosome. Names ignored. vector provided contains less colours number chromosomes plot, values recycled. NULL, default, colours automatically chosen predefined palette. ncol Integer, number Manhattan plots per row several GWAS results provided.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/manhattan_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Creates a Manhattan plot — manhattan_plot","text":"ggplot.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/manhattan_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Creates a Manhattan plot — manhattan_plot","text":"","code":"if (interactive()){ x <- get_example_data()[[\"GWAS\"]] manhattan_plot(x) ## Adding a significance threshold line in the plot manhattan_plot(x, score_thr = 4) ## Use only two colours for the chromosomes manhattan_plot(x, score_thr = 4, chrom_col = c(\"dodgerblue1\", \"dodgerblue4\")) }"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_CAN_data.html","id":null,"dir":"Reference","previous_headings":"","what":"CAN_data constructor — new_CAN_data","title":"CAN_data constructor — new_CAN_data","text":"CAN_data constructor","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_CAN_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"CAN_data constructor — new_CAN_data","text":"","code":"new_CAN_data(dat)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_CAN_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"CAN_data constructor — new_CAN_data","text":"dat Tibble, containing information genes interest, least columns chromosome, start, end, position name.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_CAN_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"CAN_data constructor — new_CAN_data","text":"CAN_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_CUSTOM_data.html","id":null,"dir":"Reference","previous_headings":"","what":"CUSTOM_data constructor — new_CUSTOM_data","title":"CUSTOM_data constructor — new_CUSTOM_data","text":"CUSTOM_data constructor","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_CUSTOM_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"CUSTOM_data constructor — new_CUSTOM_data","text":"","code":"new_CUSTOM_data(dat)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_CUSTOM_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"CUSTOM_data constructor — new_CUSTOM_data","text":"dat Tibble, custom genomic features, least columns chromosome, position score.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_CUSTOM_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"CUSTOM_data constructor — new_CUSTOM_data","text":"GWAS_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_DE_data.html","id":null,"dir":"Reference","previous_headings":"","what":"DE_data constructor — new_DE_data","title":"DE_data constructor — new_DE_data","text":"DE_data constructor","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_DE_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"DE_data constructor — new_DE_data","text":"","code":"new_DE_data(dat)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_DE_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"DE_data constructor — new_DE_data","text":"dat Tibble, results differential expression analysis, least columns chromosome, score, log2FoldChange, start, end position.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_DE_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"DE_data constructor — new_DE_data","text":"DE_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_GWAS_data.html","id":null,"dir":"Reference","previous_headings":"","what":"GWAS_data constructor — new_GWAS_data","title":"GWAS_data constructor — new_GWAS_data","text":"GWAS_data constructor","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_GWAS_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"GWAS_data constructor — new_GWAS_data","text":"","code":"new_GWAS_data(dat)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_GWAS_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"GWAS_data constructor — new_GWAS_data","text":"dat Tibble, results GWAS analysis, least columns chromosome, position score.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/new_GWAS_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"GWAS_data constructor — new_GWAS_data","text":"GWAS_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/run_hidecan_shiny.html","id":null,"dir":"Reference","previous_headings":"","what":"Launches the HIDECAN shiny app — run_hidecan_shiny","title":"Launches the HIDECAN shiny app — run_hidecan_shiny","text":"Starts HIDECAN shiny app. app reads csv data produce HIDECAN plot.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/run_hidecan_shiny.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Launches the HIDECAN shiny app — run_hidecan_shiny","text":"","code":"run_hidecan_shiny()"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/run_hidecan_shiny.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Launches the HIDECAN shiny app — run_hidecan_shiny","text":"return value, called side effects (launching shiny app).","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_CAN_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Checks validity of input for CAN_data constructor — validate_CAN_data","title":"Checks validity of input for CAN_data constructor — validate_CAN_data","text":"Checks validity input CAN_data constructor","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_CAN_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Checks validity of input for CAN_data constructor — validate_CAN_data","text":"","code":"validate_CAN_data(x)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_CAN_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Checks validity of input for CAN_data constructor — validate_CAN_data","text":"x, CAN_data object constructed via new_CAN_data.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_CAN_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Checks validity of input for CAN_data constructor — validate_CAN_data","text":"CAN_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_CUSTOM_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Checks validity of input for CUSTOM_data constructor — validate_CUSTOM_data","title":"Checks validity of input for CUSTOM_data constructor — validate_CUSTOM_data","text":"Checks validity input CUSTOM_data constructor","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_CUSTOM_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Checks validity of input for CUSTOM_data constructor — validate_CUSTOM_data","text":"","code":"validate_CUSTOM_data(x)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_CUSTOM_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Checks validity of input for CUSTOM_data constructor — validate_CUSTOM_data","text":"x, CUSTOM_data object constructed via new_CUSTOM_data.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_CUSTOM_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Checks validity of input for CUSTOM_data constructor — validate_CUSTOM_data","text":"CUSTOM_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_DE_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Checks validity of input for DE_data constructor — validate_DE_data","title":"Checks validity of input for DE_data constructor — validate_DE_data","text":"Checks validity input DE_data constructor","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_DE_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Checks validity of input for DE_data constructor — validate_DE_data","text":"","code":"validate_DE_data(x)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_DE_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Checks validity of input for DE_data constructor — validate_DE_data","text":"x, DE_data object constructed via new_DE_data.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_DE_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Checks validity of input for DE_data constructor — validate_DE_data","text":"DE_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_GWAS_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Checks validity of input for GWAS_data constructor — validate_GWAS_data","title":"Checks validity of input for GWAS_data constructor — validate_GWAS_data","text":"Checks validity input GWAS_data constructor","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_GWAS_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Checks validity of input for GWAS_data constructor — validate_GWAS_data","text":"","code":"validate_GWAS_data(x)"},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_GWAS_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Checks validity of input for GWAS_data constructor — validate_GWAS_data","text":"x, GWAS_data object constructed via new_GWAS_data.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/reference/validate_GWAS_data.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Checks validity of input for GWAS_data constructor — validate_GWAS_data","text":"GWAS_data object, .e. tibble.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/news/index.html","id":"hidecan-1109000","dir":"Changelog","previous_headings":"","what":"hidecan 1.1.0.9000","title":"hidecan 1.1.0.9000","text":"Added manhattan_plot() function generate Manhattan plots table GWAS results. Fixed bug specifying chromosome limits hidecan_plot_from_gwaspoly() mess ordering chromosomes plot.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/news/index.html","id":"changes-to-enable-custom-tracks-1-1-0-9000","dir":"Changelog","previous_headings":"","what":"Changes to enable custom tracks","title":"hidecan 1.1.0.9000","text":"New S3 classes store custom genomic features: CUSTOM_data CUSTOM_data_thr. create_hidecan_plot() now accepts CUSTOM_data_thr objects input, allows users add custom tracks plot. additional argument custom_aes handle aesthetics custom tracks. Added hidecan_aes() function returns default aesthetics different types data plot.","code":""},{"path":"https://plantandfoodresearch.github.io/hidecan/news/index.html","id":"hidecan-110","dir":"Changelog","previous_headings":"","what":"hidecan 1.1.0","title":"hidecan 1.1.0","text":"CRAN release: 2023-02-10 Removed get_gwaspoly_example_data() function package doesn’t depend GWASpoly (CRAN submission) Saved example object previously returned get_gwaspoly_example_data() rda file extdata folder","code":""}] diff --git a/sitemap.xml b/sitemap.xml index 1a238e8..f78cf41 100644 --- a/sitemap.xml +++ b/sitemap.xml @@ -5,12 +5,14 @@ https://plantandfoodresearch.github.io/hidecan/articles/hidecan-step-by-step.html https://plantandfoodresearch.github.io/hidecan/articles/hidecan.html https://plantandfoodresearch.github.io/hidecan/articles/index.html +https://plantandfoodresearch.github.io/hidecan/articles/web_only/custom_tracks.html https://plantandfoodresearch.github.io/hidecan/articles/web_only/gwaspoly_output.html https://plantandfoodresearch.github.io/hidecan/articles/web_only/shiny-app.html https://plantandfoodresearch.github.io/hidecan/authors.html https://plantandfoodresearch.github.io/hidecan/index.html https://plantandfoodresearch.github.io/hidecan/news/index.html https://plantandfoodresearch.github.io/hidecan/reference/CAN_data.html +https://plantandfoodresearch.github.io/hidecan/reference/CUSTOM_data.html https://plantandfoodresearch.github.io/hidecan/reference/DE_data.html https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data.html https://plantandfoodresearch.github.io/hidecan/reference/GWAS_data_from_gwaspoly.html @@ -18,18 +20,27 @@ https://plantandfoodresearch.github.io/hidecan/reference/combine_chrom_length.html https://plantandfoodresearch.github.io/hidecan/reference/compute_chrom_length.html https://plantandfoodresearch.github.io/hidecan/reference/create_hidecan_plot.html +https://plantandfoodresearch.github.io/hidecan/reference/dot-add_data_type.html +https://plantandfoodresearch.github.io/hidecan/reference/dot-check_chrom_limits.html +https://plantandfoodresearch.github.io/hidecan/reference/dot-check_chroms.html https://plantandfoodresearch.github.io/hidecan/reference/dot-check_cols.html https://plantandfoodresearch.github.io/hidecan/reference/dot-compute_chrom_length_genes.html +https://plantandfoodresearch.github.io/hidecan/reference/dot-compute_chrom_length_markers.html +https://plantandfoodresearch.github.io/hidecan/reference/dot-get_aes_type.html +https://plantandfoodresearch.github.io/hidecan/reference/dot-get_plot_aes.html https://plantandfoodresearch.github.io/hidecan/reference/get_example_data.html +https://plantandfoodresearch.github.io/hidecan/reference/hidecan_aes.html https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot.html https://plantandfoodresearch.github.io/hidecan/reference/hidecan_plot_from_gwaspoly.html https://plantandfoodresearch.github.io/hidecan/reference/index.html https://plantandfoodresearch.github.io/hidecan/reference/manhattan_plot.html https://plantandfoodresearch.github.io/hidecan/reference/new_CAN_data.html +https://plantandfoodresearch.github.io/hidecan/reference/new_CUSTOM_data.html https://plantandfoodresearch.github.io/hidecan/reference/new_DE_data.html https://plantandfoodresearch.github.io/hidecan/reference/new_GWAS_data.html https://plantandfoodresearch.github.io/hidecan/reference/run_hidecan_shiny.html https://plantandfoodresearch.github.io/hidecan/reference/validate_CAN_data.html +https://plantandfoodresearch.github.io/hidecan/reference/validate_CUSTOM_data.html https://plantandfoodresearch.github.io/hidecan/reference/validate_DE_data.html https://plantandfoodresearch.github.io/hidecan/reference/validate_GWAS_data.html

    Usage # S3 method for class 'CAN_data' apply_threshold(x, score_thr = 0, log2fc_thr = 0) +# S3 method for class 'CUSTOM_data' +apply_threshold(x, score_thr = 0, log2fc_thr = 0) + # Default S3 method apply_threshold(x, score_thr = 0, log2fc_thr = 0) @@ -74,7 +78,7 @@

    Argumentsx -

    Either a GWAS_data, DE_data or CAN_data object.

    +

    Either a GWAS_data, DE_data, CAN_data or CUSTOM_data object.

    score_thr
    @@ -87,13 +91,13 @@

    Arguments

    Value

    -

    A filtered tibble (of class GWAS_data_thr, DE_data_thr or -CAN_data_thr).

    +

    A filtered tibble (of class GWAS_data_thr, DE_data_thr, +CAN_data_thr or CUSTOM_data_thr).

    @@ -171,7 +175,7 @@

    Examples -

    Site built with pkgdown 2.1.0.

    +

    Site built with pkgdown 2.1.1.

    diff --git a/reference/combine_chrom_length.html b/reference/combine_chrom_length.html index e2fb180..1a33365 100644 --- a/reference/combine_chrom_length.html +++ b/reference/combine_chrom_length.html @@ -23,6 +23,7 @@ @@ -56,7 +57,7 @@

    Argumentsx -

    A list of GWAS_data, DE_data or CAN_data objects.

    +

    A list of GWAS_data, DE_data, CAN_data or CUSTOM_data objects.

    @@ -100,7 +101,7 @@

    Examples -

    Site built with pkgdown 2.1.0.

    +

    Site built with pkgdown 2.1.1.

    diff --git a/reference/compute_chrom_length.CUSTOM_data.html b/reference/compute_chrom_length.CUSTOM_data.html new file mode 100644 index 0000000..fd0af0e --- /dev/null +++ b/reference/compute_chrom_length.CUSTOM_data.html @@ -0,0 +1,8 @@ + + + + + + + + diff --git a/reference/compute_chrom_length.html b/reference/compute_chrom_length.html index 0e8a9a6..5da0863 100644 --- a/reference/compute_chrom_length.html +++ b/reference/compute_chrom_length.html @@ -23,6 +23,7 @@ @@ -57,6 +58,9 @@

    Usage compute_chrom_length(x) # S3 method for class 'CAN_data' +compute_chrom_length(x) + +# S3 method for class 'CUSTOM_data' compute_chrom_length(x) @@ -65,7 +69,7 @@

    Argumentsx -

    Either a GWAS_data, DE_data or CAN_data object.

    +

    Either a GWAS_data, DE_data, CAN_data or CUSTOM_data object.

    @@ -134,7 +138,7 @@

    Examples -

    Site built with pkgdown 2.1.0.

    +

    Site built with pkgdown 2.1.1.

    diff --git a/reference/create_hidecan_plot.html b/reference/create_hidecan_plot.html index e3aed1b..5f2764f 100644 --- a/reference/create_hidecan_plot.html +++ b/reference/create_hidecan_plot.html @@ -23,6 +23,7 @@ @@ -62,7 +63,8 @@

    Usage legend_position = "bottom", point_size = 3, label_size = 3.5, - label_padding = 0.15 + label_padding = 0.15, + custom_aes = NULL ) @@ -71,9 +73,10 @@

    Argumentsx -

    A list of GWAS_data_thr, DE_data_thr and/or CAN_data_thr -produced by the apply_threshold() function. If named, the names -will be appended to the y-axis labels (use ' ' as empty name in the list).

    +

    A list of GWAS_data_thr, DE_data_thr, CAN_data_thr and/or +CUSTOM_data_thr produced by the apply_threshold() function. +If named, the names will be appended to the y-axis labels (use ' ' as +empty name in the list).

    chrom_length
    @@ -147,6 +150,13 @@

    Argumentsgeom_label_repel).

    + +
    custom_aes
    +

    Named list of plot aesthetics for custom data types. See +hidecan_aes() for information about the content of each element. Default +is NULL (only needed if there are CUSTOM_data_thr objects in x or to +customise the aesthetics for the default data tracks).

    +

    Value

    @@ -215,7 +225,7 @@

    Examples -

    Site built with pkgdown 2.1.0.

    +

    Site built with pkgdown 2.1.1.

    diff --git a/reference/dot-add_data_type.html b/reference/dot-add_data_type.html new file mode 100644 index 0000000..a02bc0b --- /dev/null +++ b/reference/dot-add_data_type.html @@ -0,0 +1,124 @@ + +Add data type to HIDECAN plot — .add_data_type • hidecan + Skip to contents + + +
    +
    +
    + +
    +

    Add data type to HIDECAN plot

    +
    + +
    +

    Usage

    +
    .add_data_type(
    +  p,
    +  toplot,
    +  i,
    +  paes,
    +  add_new_legend,
    +  point_size,
    +  label_size,
    +  label_padding
    +)
    +
    + +
    +

    Arguments

    + + +
    p
    +

    Current ggplot.

    + + +
    toplot
    +

    Tibble of data to plot.

    + + +
    i
    +

    Character, data type to add in the plot.

    + + +
    paes
    +

    Named list, aesthetics to use for this data type (see +hidecan_aes() for information about the required values).

    + + +
    add_new_legend
    +

    Logical, whether the current data type requires a new +legend for fill.

    + + +
    point_size
    +

    Numeric, size of the points in the plot.

    + + +
    label_size
    +

    Numeric, size of the gene labels in the plot.

    + + +
    label_padding
    +

    Numeric, amount of padding around gene labels in the +plot, as unit or number.

    + +
    +
    +

    Value

    +

    Ggplot p to which the new data type has been added.

    +
    + +
    + + +
    + + + +
    + + + + + + + diff --git a/reference/dot-check_chrom_limits.html b/reference/dot-check_chrom_limits.html new file mode 100644 index 0000000..5fbbfa0 --- /dev/null +++ b/reference/dot-check_chrom_limits.html @@ -0,0 +1,98 @@ + +Check chromosome limits — .check_chrom_limits • hidecan + Skip to contents + + +
    +
    +
    + +
    +

    Check chromosome limits

    +
    + +
    +

    Usage

    +
    .check_chrom_limits(chrom_limits, chrom_length, chroms)
    +
    + +
    +

    Arguments

    + + +
    chrom_limits
    +

    Integer vector of length 2, or named list where the +elements are integer vectors of length 2. If vector, gives the lower and +upper limit of the chromosomes (in bp) to use in the plot. If a named list, +names should correspond to chromosome names. Gives for each chromosome the +lower and upper limits (in bp) to use in the plot. Doesn't have to be +specified for all chromosomes. Default value is NULL, i.e. no limits are +applied to the chromosomes (they will be plotted in their entirety).

    + + +
    chrom_length
    +

    Tibble of chromosome length.

    + + +
    chroms
    +

    Character vector, name of chromosomes to include in the plot.

    + +
    +
    +

    Value

    +

    Tibble of chromosome limits to use in the plot.

    +
    + +
    + + +
    + + + +
    + + + + + + + diff --git a/reference/dot-check_chroms.html b/reference/dot-check_chroms.html new file mode 100644 index 0000000..4e29fd6 --- /dev/null +++ b/reference/dot-check_chroms.html @@ -0,0 +1,99 @@ + +Check chromosomes to plot — .check_chroms • hidecan + Skip to contents + + +
    +
    +
    + +
    +

    Check chromosomes to plot

    +
    + +
    +

    Usage

    +
    .check_chroms(toplot, chrom_length, chroms, remove_empty_chrom)
    +
    + +
    +

    Arguments

    + + +
    toplot
    +

    Tibble, main data-frame for plot.

    + + +
    chrom_length
    +

    Tibble of chromosome length.

    + + +
    chroms
    +

    Character vector, name of chromosomes to include in the plot. +If NULL (default value), all chromosomes will be included.

    + + +
    remove_empty_chrom
    +

    Logical, should chromosomes with no significant +markers/genes nor candidate genes be removed from the plot? Default value +if FALSE.

    + +
    +
    +

    Value

    +

    Character vector of chromosomes to plot.

    +
    + +
    + + +
    + + + +
    + + + + + + + diff --git a/reference/dot-check_cols.html b/reference/dot-check_cols.html index 97908af..2bb05bf 100644 --- a/reference/dot-check_cols.html +++ b/reference/dot-check_cols.html @@ -21,6 +21,7 @@ @@ -78,7 +79,7 @@

    Value

    diff --git a/reference/dot-compute_chrom_length_genes.html b/reference/dot-compute_chrom_length_genes.html index bd83a14..ef978ba 100644 --- a/reference/dot-compute_chrom_length_genes.html +++ b/reference/dot-compute_chrom_length_genes.html @@ -23,6 +23,7 @@ @@ -74,7 +75,7 @@

    Value

    diff --git a/reference/dot-compute_chrom_length_markers.html b/reference/dot-compute_chrom_length_markers.html new file mode 100644 index 0000000..332b364 --- /dev/null +++ b/reference/dot-compute_chrom_length_markers.html @@ -0,0 +1,88 @@ + +Computes chromosomes' length for a tibble of markers — .compute_chrom_length_markers • hidecan + Skip to contents + + +
    +
    +
    + +
    +

    Computes the length (in bp) of each chromosome as the maximum +position of chromosomes on the chromosome.

    +
    + +
    +

    Usage

    +
    .compute_chrom_length_markers(x)
    +
    + +
    +

    Arguments

    + + +
    x
    +

    Either a GWAS_data or CUSTOM_data object.

    + +
    +
    +

    Value

    +

    A tibble with two columns: chromosome (chromosome name) and +length (chromosome length in base pair).

    +
    + +
    + + +
    + + + +
    + + + + + + + diff --git a/reference/dot-get_aes_type.html b/reference/dot-get_aes_type.html new file mode 100644 index 0000000..8b00f16 --- /dev/null +++ b/reference/dot-get_aes_type.html @@ -0,0 +1,85 @@ + +Returns either "aes_type" attribute or object class — .get_aes_type • hidecan + Skip to contents + + +
    +
    +
    + +
    +

    Returns either "aes_type" attribute or object class

    +
    + +
    +

    Usage

    +
    .get_aes_type(x)
    +
    + +
    +

    Arguments

    + + +
    x
    +

    A GWAS_data_thr, DE_data_thr, CAN_data_thr or +CUSTOM_data_thr object.

    + +
    +
    +

    Value

    +

    Either "aes_type" attribute or object class.

    +
    + +
    + + +
    + + + +
    + + + + + + + diff --git a/reference/dot-get_plot_aes.html b/reference/dot-get_plot_aes.html new file mode 100644 index 0000000..8237046 --- /dev/null +++ b/reference/dot-get_plot_aes.html @@ -0,0 +1,95 @@ + +Computes plot aesthetics — .get_plot_aes • hidecan + Skip to contents + + +
    +
    +
    + +
    +

    Get the list of aesthetics for each data types in the plot.

    +
    + +
    +

    Usage

    +
    .get_plot_aes(aes_types, colour_genes_by_score, custom_aes)
    +
    + +
    +

    Arguments

    + + +
    aes_types
    +

    Character vector of data types (one per dataset to plot), +should be computed with .get_aes_type().

    + + +
    colour_genes_by_score
    +

    Logical, whether to colour the genes by score +(TRUE) or by log2(fold-change) (FALSE).

    + + +
    custom_aes
    +

    Named list of plot aesthetics for custom data types. See +hidecan_aes() for information about the content of each element.

    + +
    +
    +

    Value

    +

    Named list of plot aesthetics.

    +
    + +
    + + +
    + + + +
    + + + + + + + diff --git a/reference/get_example_data.html b/reference/get_example_data.html index edbd4de..1a9f5ef 100644 --- a/reference/get_example_data.html +++ b/reference/get_example_data.html @@ -21,6 +21,7 @@ @@ -95,7 +96,7 @@

    Details diff --git a/reference/hidecan_aes.html b/reference/hidecan_aes.html new file mode 100644 index 0000000..5dc0616 --- /dev/null +++ b/reference/hidecan_aes.html @@ -0,0 +1,92 @@ + +Default aesthetics for HIDECAN plot — hidecan_aes • hidecan + Skip to contents + + +
    +
    +
    + +
    +

    Generates a list of the default aesthetics used for HIDECAN plots.

    +
    + +
    +

    Usage

    +
    hidecan_aes(colour_genes_by_score = TRUE)
    +
    + +
    +

    Arguments

    + + +
    colour_genes_by_score
    +

    Logical, whether to colour the genes by score +(TRUE) or by log2(fold-change) (FALSE). Default value is TRUE.

    + +
    +
    +

    Value

    +

    A named list, with one element per type of data (e.g. GWAS, DE, etc). +Each element is itself a list with the following elements:

    • y_label: prefix added to the name of a track on the y-axis of the plot.

    • +
    • line_colour: colour of the vertical line used to show the position of +elements of this type.

    • +
    • point_shape: shape used for the points of this type.

    • +
    • show_name: whether a label with name value should be added to points of +this type.

    • +
    • fill_scale: fill scale to use for the points of this type.

    • +
    + +
    + + +
    + + + +
    + + + + + + + diff --git a/reference/hidecan_plot.html b/reference/hidecan_plot.html index fe5077d..59e072e 100644 --- a/reference/hidecan_plot.html +++ b/reference/hidecan_plot.html @@ -1,7 +1,7 @@ -Wrapper to create a HIDECAN plot — hidecan_plot • hidecan +Wrapper to create a HIDECAN plot — hidecan_plot • hidecan Skip to contents @@ -23,6 +23,7 @@ @@ -42,8 +43,8 @@
    -

    Wrapper function to create a HIDECAN plot from GWAS results, -DE results or candidate genes.

    +

    Wrapper function to create a HIDECAN plot from GWAS results, DE results or +candidate genes.

    @@ -82,10 +86,10 @@

    Argumentsde_list -

    Data-frame or list of data-frames containing DE results, -each with at least a chromosome, start, end, log2FoldChange and -either padj or score columns. If a named list, the names will be used in -the plot.

    +

    Data-frame or list of data-frames containing DE results, each +with at least a chromosome, start, end, log2FoldChange and either +padj or score columns. If a named list, the names will be used in the +plot.

    can_list
    @@ -95,13 +99,13 @@

    Argumentsscore_thr_gwas -

    Numeric, the score threshold for GWAS results that will be used to -select which markers will be plotted. Default value is 4.

    +

    Numeric, the score threshold for GWAS results that will +be used to select which markers will be plotted. Default value is 4.

    score_thr_de
    -

    Numeric, the score threshold for DE results that will be used to -select which markers will be plotted. Default value is 2.

    +

    Numeric, the score threshold for DE results that will be +used to select which markers will be plotted. Default value is 2.

    log2fc_thr
    @@ -180,6 +184,25 @@

    Argumentsgeom_label_repel).

    + +
    custom_aes
    +

    Named list of plot aesthetics for custom data types. See +hidecan_aes() for information about the content of each element. Default +is NULL (only needed if there are CUSTOM_data_thr objects in x or to +customise the aesthetics for the default data tracks).

    + + +
    custom_list
    +

    Data-frame or list of data-frames containing custom +genomic features, each with at least a chromosome, position and score +columns. If a named list, the names will be used in the plot.

    + + +
    score_thr_custom
    +

    Numeric, the score threshold for custom genomic +features that will be used to select which markers will be plotted. Default +value is 0.

    +

    Value

    @@ -243,7 +266,7 @@

    Examples -

    Site built with pkgdown 2.1.0.

    +

    Site built with pkgdown 2.1.1.

    diff --git a/reference/hidecan_plot_from_gwaspoly.html b/reference/hidecan_plot_from_gwaspoly.html index 6e4c21a..e2b31f7 100644 --- a/reference/hidecan_plot_from_gwaspoly.html +++ b/reference/hidecan_plot_from_gwaspoly.html @@ -21,6 +21,7 @@ @@ -86,7 +87,7 @@

    Value

    diff --git a/reference/index.html b/reference/index.html index 3e21bb8..5dbff92 100644 --- a/reference/index.html +++ b/reference/index.html @@ -21,6 +21,7 @@ @@ -56,6 +57,12 @@

    Internal constructorsCAN_data constructor
    + new_CUSTOM_data() + +
    +
    CUSTOM_data constructor
    +
    + new_DE_data()
    @@ -74,6 +81,12 @@

    Internal constructorsChecks validity of input for CAN_data constructor

    + validate_CUSTOM_data() + +
    +
    Checks validity of input for CUSTOM_data constructor
    +
    + validate_DE_data()
    @@ -113,6 +126,12 @@

    Constructors from tibbles
    Creates a CAN_data object
    +

    + + CUSTOM_data() + +
    +
    Creates a CUSTOM_data object

    Constructors from packages output

    @@ -155,6 +174,12 @@

    Computing chromosome length.compute_chrom_length_markers() + + +
    Computes chromosomes' length for a tibble of markers
    +
    + .compute_chrom_length_genes()
    @@ -201,6 +226,12 @@

    Plotting functionshidecan_aes() + + +
    Default aesthetics for HIDECAN plot
    +

    + run_hidecan_shiny()
    @@ -217,6 +248,24 @@

    Plotting functions.get_aes_type() + + +
    Returns either "aes_type" attribute or object class
    +

    + + .get_plot_aes() + +
    +
    Computes plot aesthetics
    +
    + + .add_data_type() + +
    +
    Add data type to HIDECAN plot

    Example datasets

    @@ -251,6 +300,18 @@

    Utils

    Checks whether some columns are present in a tibble
    +
    + + .check_chroms() + +
    +
    Check chromosomes to plot
    +
    + + .check_chrom_limits() + +
    +
    Check chromosome limits
    @@ -261,7 +322,7 @@

    Utils

    diff --git a/reference/manhattan_plot.html b/reference/manhattan_plot.html index c52eae8..a511199 100644 --- a/reference/manhattan_plot.html +++ b/reference/manhattan_plot.html @@ -21,6 +21,7 @@ @@ -139,7 +140,7 @@