From b7b4ee9aeea2e1d58db350fee84f5caf8ec8f483 Mon Sep 17 00:00:00 2001 From: Giulio Benedetti Date: Thu, 31 Oct 2024 20:00:52 +0200 Subject: [PATCH 1/3] Add tests --- DESCRIPTION | 2 - NEWS | 3 +- R/landing_page.R | 208 ++++++++++++++++---------------- R/miaDash.R | 2 + R/observers.R | 8 ++ R/outputs.R | 4 + R/utils.R | 39 ++++-- man/utils.Rd | 40 ++++++ tests/testthat.R | 12 ++ tests/testthat/test-observers.R | 22 ++++ tests/testthat/test-outputs.R | 13 ++ tests/testthat/test-utils.R | 12 ++ vignettes/miaDash.Rmd | 14 ++- 13 files changed, 261 insertions(+), 118 deletions(-) create mode 100644 man/utils.Rd create mode 100644 tests/testthat.R create mode 100644 tests/testthat/test-observers.R create mode 100644 tests/testthat/test-outputs.R create mode 100644 tests/testthat/test-utils.R diff --git a/DESCRIPTION b/DESCRIPTION index b804cc9..12c8275 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -44,8 +44,6 @@ Suggests: remotes, rmarkdown, testthat (>= 3.0.0) -Remotes: - github::microbiome/iSEEtree URL: https://github.com/RiboRings/miaDash BugReports: https://github.com/RiboRings/miaDash/issues Roxygen: list(markdown = TRUE) diff --git a/NEWS b/NEWS index 5d97d88..a23d0b5 100644 --- a/NEWS +++ b/NEWS @@ -5,4 +5,5 @@ Changes in version 0.1.0 Changes in version 0.2.0 * Added manipulate functionality * Added estimate functionality -* Added panel layout customisation \ No newline at end of file +* Added panel layout customisation +* Added unit testing diff --git a/R/landing_page.R b/R/landing_page.R index 0b549f5..8e18f28 100644 --- a/R/landing_page.R +++ b/R/landing_page.R @@ -18,10 +18,8 @@ #' @importFrom shinyjs disable #' @importFrom utils data .landing_page <- function(FUN, input, output, session) { - - mia_datasets <- data(package = "mia") - mia_datasets <- mia_datasets$results[-c(2, 5), "Item"] - data(list = mia_datasets, package = "mia") + + mia_datasets <- .import_datasets(-c(2, 5)) # nocov start output$allPanels <- renderUI({ @@ -30,7 +28,7 @@ fluidRow(column(4, wellPanel(id = "import.panel", - titlePanel("Import"), + titlePanel("Import"), tabsetPanel(id = "format", @@ -60,159 +58,157 @@ fileInput(inputId = "rowdata", label = "rowData:", accept = ".csv") - ), + ), - tabPanel(title = "Foreign", value = "foreign", + tabPanel(title = "Foreign", value = "foreign", - radioButtons(inputId = "ftype", - label = "Type:", choices = list("biom", "QZA", - "MetaPhlAn")), + radioButtons(inputId = "ftype", + label = "Type:", choices = list("biom", "QZA", + "MetaPhlAn")), - fileInput(inputId = "main.file", - label = "Main file:", accept = c(".biom", - ".QZA", ".txt")), + fileInput(inputId = "main.file", + label = "Main file:", accept = c(".biom", + ".QZA", ".txt")), - conditionalPanel( - condition = "input.ftype == 'biom'", + conditionalPanel( + condition = "input.ftype == 'biom'", - checkboxInput(inputId = "rm.tax.pref", - label = "Remove taxa prefixes"), + checkboxInput(inputId = "rm.tax.pref", + label = "Remove taxa prefixes"), - checkboxInput(inputId = "rank.from.pref", - label = "Derive taxa from prefixes") - ), + checkboxInput(inputId = "rank.from.pref", + label = "Derive taxa from prefixes") + ), - conditionalPanel( - condition = "input.ftype == 'MetaPhlAn'", + conditionalPanel( + condition = "input.ftype == 'MetaPhlAn'", - fileInput(inputId = "col.data", label = "colData:", - accept = ".tsv"), + fileInput(inputId = "col.data", label = "colData:", + accept = ".tsv"), - fileInput(inputId = "tree.file", label = "Tree:", - accept = ".tree") - ) + fileInput(inputId = "tree.file", label = "Tree:", + accept = ".tree") + ) - ) + ) - ), + ), - actionButton("import", "Upload", class = "btn-success", - style = .actionbutton_biocstyle) + actionButton("import", "Upload", class = "btn-success", + style = .actionbutton_biocstyle) - )), + )), column(4, wellPanel(id = "manipulate.panel", - titlePanel("Manipulate"), + titlePanel("Manipulate"), - tabsetPanel(id = "manipulate", + tabsetPanel(id = "manipulate", - tabPanel(title = "Subset", value = "subset", + tabPanel(title = "Subset", value = "subset", - radioButtons(inputId = "subkeep", label = "Keep:", - choices = c("prevalent", "rare"), inline = TRUE), + radioButtons(inputId = "subkeep", label = "Keep:", + choices = c("prevalent", "rare"), inline = TRUE), - selectInput(inputId = "subassay", label = "Assay:", - choices = NULL), + selectInput(inputId = "subassay", label = "Assay:", + choices = NULL), - sliderInput(inputId = "prevalence", value = 0, - label = "Prevalence threshold:", step = 0.01, - min = 0, max = 1), + sliderInput(inputId = "prevalence", value = 0, + label = "Prevalence threshold:", step = 0.01, + min = 0, max = 1), - numericInput(inputId = "detection", value = 0, - label = "Detection threshold:", min = 0, step = 1) + numericInput(inputId = "detection", value = 0, + label = "Detection threshold:", min = 0, step = 1) - ), + ), - tabPanel(title = "Agglomerate", value = "agglomerate", + tabPanel(title = "Agglomerate", value = "agglomerate", - selectInput(inputId = "taxrank", label = "Taxonomic rank:", - choices = NULL) + selectInput(inputId = "taxrank", + label = "Taxonomic rank:", choices = NULL) - ), + ), - tabPanel(title = "Transform", value = "transform", + tabPanel(title = "Transform", value = "transform", - selectInput(inputId = "assay.type", label = "Assay:", - choices = NULL), + selectInput(inputId = "assay.type", label = "Assay:", + choices = NULL), - selectInput(inputId = "trans.method", label = "Method:", - choices = c("relabundance", "clr", "standardize")), + selectInput(inputId = "trans.method", label = "Method:", + choices = c("relabundance", "clr", "standardize")), - checkboxInput(inputId = "pseudocount", - label = "Pseudocount"), + checkboxInput(inputId = "pseudocount", + label = "Pseudocount"), - textInput(inputId = "assay.name", label = "Name:"), + textInput(inputId = "assay.name", label = "Name:"), - radioButtons(inputId = "margin", label = "Margin:", - choices = c("samples", "features"), inline = TRUE) + radioButtons(inputId = "margin", label = "Margin:", + choices = c("samples", "features"), inline = TRUE) - )), + )), - actionButton("apply", "Apply", class = "btn-success", - style = .actionbutton_biocstyle) + actionButton("apply", "Apply", class = "btn-success", + style = .actionbutton_biocstyle) )), column(4, wellPanel(id = "estimate.panel", - titlePanel("Estimate"), + titlePanel("Estimate"), - tabsetPanel(id = "estimate", + tabsetPanel(id = "estimate", - tabPanel(title = "Alpha", value = "alpha", + tabPanel(title = "Alpha", value = "alpha", - selectInput(inputId = "alpha.assay", label = "Assay:", - choices = NULL), + selectInput(inputId = "alpha.assay", label = "Assay:", + choices = NULL), - selectInput(inputId = "alpha.index", label = "Metric:", - choices = c("coverage", "shannon", "faith"), - multiple = TRUE), + selectInput(inputId = "alpha.index", label = "Metric:", + choices = c("coverage", "shannon", "faith"), + multiple = TRUE), - textInput(inputId = "alpha.name", label = "Name:") + textInput(inputId = "alpha.name", label = "Name:") - ), + ), - tabPanel(title = "Beta", value = "beta", + tabPanel(title = "Beta", value = "beta", - radioButtons(inputId = "bmethod", label = "Method:", - choices = c("MDS", "NMDS", "PCA", "RDA"), inline = TRUE), + radioButtons(inputId = "bmethod", label = "Method:", + choices = c("MDS", "NMDS", "PCA", "RDA"), + inline = TRUE), - - selectInput(inputId = "beta.assay", label = "Assay:", - choices = NULL), + selectInput(inputId = "beta.assay", label = "Assay:", + choices = NULL), - conditionalPanel( - condition = "input.bmethod != 'PCA'", + conditionalPanel( + condition = "input.bmethod != 'PCA'", - selectInput(inputId = "beta.index", label = "Metric:", - choices = c("euclidean", "bray", "jaccard", "unifrac")), - ), + selectInput(inputId = "beta.index", label = "Metric:", + choices = c("euclidean", "bray", "jaccard", "unifrac")), + ), - conditionalPanel( - condition = "input.bmethod == 'RDA'", + conditionalPanel( + condition = "input.bmethod == 'RDA'", - textInput(inputId = "rda.formula", label = "Formula:", - placeholder = "data ~ var1 + var2 * var3"), - ), + textInput(inputId = "rda.formula", label = "Formula:", + placeholder = "data ~ var1 + var2 * var3"), + ), - numericInput(inputId = "ncomponents", value = 5, - label = "Number of components:", min = 1, step = 1), + numericInput(inputId = "ncomponents", value = 5, + label = "Number of components:", min = 1, step = 1), - textInput(inputId = "beta.name", label = "Name:") + textInput(inputId = "beta.name", label = "Name:") - ) + ) - ), + ), - actionButton("compute", "Compute", class = "btn-success", - style = .actionbutton_biocstyle) + actionButton("compute", "Compute", class = "btn-success", + style = .actionbutton_biocstyle) ))), - fluidRow( - - column(4, wellPanel(id = "visualise.panel", + fluidRow(column(4, wellPanel(id = "visualise.panel", titlePanel("Visualise"), @@ -223,19 +219,19 @@ actionButton("launch", "Launch iSEE", class = "btn-success", style = .actionbutton_biocstyle) - )), + )), - column(8, wellPanel(id = "output.panel", + column(8, wellPanel(id = "output.panel", - titlePanel("Output"), + titlePanel("Output"), - verbatimTextOutput(outputId = "object"), + verbatimTextOutput(outputId = "object"), - downloadButton(outputId = "download", label = "Download", - style = .actionbutton_biocstyle) + downloadButton(outputId = "download", label = "Download", + style = .actionbutton_biocstyle) - ))) - ) + )) + )) }) ## Disable navbar buttons that are not linked to any observer yet diff --git a/R/miaDash.R b/R/miaDash.R index 9c26d58..e57ed22 100644 --- a/R/miaDash.R +++ b/R/miaDash.R @@ -44,6 +44,7 @@ miaDash <- function() { #' @importFrom SingleCellExperiment reducedDims .launch_isee <- function(FUN, initial, session, rObjects) { + # nocov start tse <- rObjects$tse initial <- lapply(initial, function(x) eval(parse(text = paste0(x, "()")))) @@ -68,4 +69,5 @@ miaDash <- function() { enable("iSEE_INTERNAL_citation_info") # citation info invisible(NULL) + # nocov end } \ No newline at end of file diff --git a/R/observers.R b/R/observers.R index 27f306b..814dd9b 100644 --- a/R/observers.R +++ b/R/observers.R @@ -22,6 +22,7 @@ #' @importFrom TreeSummarizedExperiment TreeSummarizedExperiment .create_import_observers <- function(input, rObjects) { + # nocov start observeEvent(input$import, { if( input$format == "dataset" ){ @@ -100,6 +101,7 @@ } }, ignoreInit = TRUE, ignoreNULL = FALSE) + # nocov end invisible(NULL) } @@ -111,6 +113,7 @@ #' transformAssay .create_manipulate_observers <- function(input, rObjects) { + # nocov start observeEvent(input$apply, { if( input$manipulate == "subset" ){ @@ -172,6 +175,7 @@ } }, ignoreInit = TRUE, ignoreNULL = TRUE) + # nocov end invisible(NULL) } @@ -185,6 +189,7 @@ #' @importFrom vegan vegdist .create_estimate_observers <- function(input, rObjects) { + # nocov start observeEvent(input$compute, { if( input$estimate == "alpha" ){ @@ -269,6 +274,7 @@ } }, ignoreInit = TRUE, ignoreNULL = TRUE) + # nocov end invisible(NULL) } @@ -280,6 +286,7 @@ #' @importFrom rintrojs introjs .update_observers <- function(input, session, rObjects){ + # nocov start observe({ if( isS4(rObjects$tse) ){ @@ -311,6 +318,7 @@ introjs(session, options = list(steps = .landing_page_tour)) }, ignoreInit = TRUE) + # nocov end invisible(NULL) } diff --git a/R/outputs.R b/R/outputs.R index ab83a9e..e0fc58a 100644 --- a/R/outputs.R +++ b/R/outputs.R @@ -16,9 +16,11 @@ #' @importFrom shiny renderPrint .render_overview <- function(output, rObjects) { + # nocov start output$object <- renderPrint({ rObjects$tse }) + # nocov end invisible(NULL) } @@ -27,10 +29,12 @@ #' @importFrom shiny downloadHandler .render_download <- function(output, rObjects) { + # nocov start output$download <- downloadHandler( filename = function() paste0("se-", Sys.Date(), ".rds"), content = function(file) saveRDS(rObjects$tse, file) ) + # nocov end invisible(NULL) } \ No newline at end of file diff --git a/R/utils.R b/R/utils.R index b142570..4aed336 100644 --- a/R/utils.R +++ b/R/utils.R @@ -1,12 +1,21 @@ -default_panels <- c("RowDataTable", "ColumnDataTable", "RowTreePlot", - "AbundancePlot", "AbundanceDensityPlot", "ReducedDimensionPlot", - "ComplexHeatmapPlot") - -other_panels <- c("LoadingPlot", "ColumnTreePlot", "RDAPlot", "ColumnDataPlot", - "RowDataPlot") +#' Utilities +#' +#' Helper functions and constants to support the app functionality. +#' +#' @name utils +#' @keywords internal -.actionbutton_biocstyle <- "color: #ffffff; background-color: #0092AC; border-color: #2e6da4" +#' @rdname utils +.import_datasets <- function(selection) { + + mia_datasets <- data(package = "mia") + mia_datasets <- mia_datasets$results[selection, "Item"] + data(list = mia_datasets, package = "mia") + + return(mia_datasets) +} +#' @rdname utils #' @importFrom shiny showModal modalDialog .print_message <- function(...){ @@ -17,6 +26,7 @@ other_panels <- c("LoadingPlot", "ColumnTreePlot", "RDAPlot", "ColumnDataPlot", } +#' @rdname utils #' @importFrom SummarizedExperiment colData .check_formula <- function(form, se){ @@ -27,6 +37,7 @@ other_panels <- c("LoadingPlot", "ColumnTreePlot", "RDAPlot", "ColumnDataPlot", return(cond) } +#' @rdname utils #' @importFrom S4Vectors isEmpty #' @importFrom methods is .check_panel <- function(se, panel_list, panel_class, panel_fun, wtext) { @@ -40,4 +51,16 @@ other_panels <- c("LoadingPlot", "ColumnTreePlot", "RDAPlot", "ColumnDataPlot", } return(panel_list) -} \ No newline at end of file +} + +#' @rdname utils +default_panels <- c("RowDataTable", "ColumnDataTable", "RowTreePlot", + "AbundancePlot", "AbundanceDensityPlot", "ReducedDimensionPlot", + "ComplexHeatmapPlot") + +#' @rdname utils +other_panels <- c("LoadingPlot", "ColumnTreePlot", "RDAPlot", "ColumnDataPlot", + "RowDataPlot") + +#' @rdname utils +.actionbutton_biocstyle <- "color: #ffffff; background-color: #0092AC; border-color: #2e6da4" diff --git a/man/utils.Rd b/man/utils.Rd new file mode 100644 index 0000000..57575d5 --- /dev/null +++ b/man/utils.Rd @@ -0,0 +1,40 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/utils.R +\docType{data} +\name{utils} +\alias{utils} +\alias{.import_datasets} +\alias{.print_message} +\alias{.check_formula} +\alias{.check_panel} +\alias{default_panels} +\alias{other_panels} +\alias{.actionbutton_biocstyle} +\title{Utilities} +\format{ +An object of class \code{character} of length 7. + +An object of class \code{character} of length 5. + +An object of class \code{character} of length 1. +} +\usage{ +.import_datasets(selection) + +.print_message(...) + +.check_formula(form, se) + +.check_panel(se, panel_list, panel_class, panel_fun, wtext) + +default_panels + +other_panels + +.actionbutton_biocstyle +} +\description{ +Helper functions and constants to support the app functionality. +} +\keyword{datasets} +\keyword{internal} diff --git a/tests/testthat.R b/tests/testthat.R new file mode 100644 index 0000000..ed3bf8e --- /dev/null +++ b/tests/testthat.R @@ -0,0 +1,12 @@ +# This file is part of the standard setup for testthat. +# It is recommended that you do not modify it. +# +# Where should you do additional test configuration? +# Learn more about the roles of various files in: +# * https://r-pkgs.org/testing-design.html#sec-tests-files-overview +# * https://testthat.r-lib.org/articles/special-files.html + +library(testthat) +library(miaDash) + +test_check("miaDash") diff --git a/tests/testthat/test-observers.R b/tests/testthat/test-observers.R new file mode 100644 index 0000000..b8a4b14 --- /dev/null +++ b/tests/testthat/test-observers.R @@ -0,0 +1,22 @@ +test_that(".create_observers works", { + + input <- new.env() + rObjects <- new.env() + FUN <- function(SE, INITIAL) invisible(NULL) + + import_out <- .create_import_observers(input, rObjects) + expect_null(import_out) + + manipulate_out <- .create_manipulate_observers(input, rObjects) + expect_null(manipulate_out) + + estimate_out <- .create_estimate_observers(input, rObjects) + expect_null(estimate_out) + + update_out <- .update_observers(input, session = NULL, rObjects) + expect_null(update_out) + + launch_out <- .create_launch_observers(FUN, input, session = NULL, rObjects) + expect_null(launch_out) + +}) diff --git a/tests/testthat/test-outputs.R b/tests/testthat/test-outputs.R new file mode 100644 index 0000000..cfd4772 --- /dev/null +++ b/tests/testthat/test-outputs.R @@ -0,0 +1,13 @@ +test_that("outputs", { + + output <- new.env() + rObjects <- new.env() + + overview_out <- .render_overview(output, rObjects) + download_out <- .render_download(output, rObjects) + + expect_null(overview_out) + expect_null(download_out) + expect_named(output, c("object", "download")) + +}) diff --git a/tests/testthat/test-utils.R b/tests/testthat/test-utils.R new file mode 100644 index 0000000..b87df3e --- /dev/null +++ b/tests/testthat/test-utils.R @@ -0,0 +1,12 @@ +test_that("utils", { + + data("Tengeler2020", package = "mia") + tse <- Tengeler2020 + + expect_equal(.import_datasets(c(1, 3)), c("GlobalPatterns", "Tengeler2020")) + + expect_true(.check_formula("data ~ patient_status + cohort", tse)) + expect_false(.check_formula("data ~ wrong_var + sample_name", tse)) + + expect_length(.check_panel(tse, c(RowDataTable()), "RowDataTable", rowData), 1) +}) diff --git a/vignettes/miaDash.Rmd b/vignettes/miaDash.Rmd index 6b0db6a..3ecd8e6 100644 --- a/vignettes/miaDash.Rmd +++ b/vignettes/miaDash.Rmd @@ -31,10 +31,21 @@ knitr::opts_chunk$set( # Introduction +The Microbiome Analysis Dashboard (miaDash) aims to make microbiome analysis +accessible to anyone, with or without programming skills. + ## Motivation ## Interface +The interface provides tools to: + +- import from datasets from several file types or practice with a ready-made + mia dataset +- manipulate objects as subsetting, agglomeration and transformation +- estimate alpha and beta diversity +- visualise different aspects with iSEEtree + # Tutorial ## Installation @@ -68,7 +79,8 @@ SCREENSHOT("screenshots/get_started.png", delay = 20) ## Citation -We hope that miaDash will be useful for your research. Please use the following information to cite the package and the overall approach. Thank you! +We hope that miaDash will be useful for your research. Please use the following +information to cite the package and the overall approach. Thank you! ```{r citation} ## Citation info From 983147ba8dae0ce4cbb0f5b7970c4d1bcd38ceee Mon Sep 17 00:00:00 2001 From: Giulio Benedetti Date: Fri, 1 Nov 2024 20:02:02 +0200 Subject: [PATCH 2/3] Finalise vignettes --- README.md | 10 +- vignettes/miaDash.Rmd | 122 ++++++++++++++++-- .../{get_started.png => dashboard.png} | Bin vignettes/screenshots/iSEEtree.png | Bin 0 -> 1026330 bytes 4 files changed, 118 insertions(+), 14 deletions(-) rename vignettes/screenshots/{get_started.png => dashboard.png} (100%) create mode 100644 vignettes/screenshots/iSEEtree.png diff --git a/README.md b/README.md index b53ed4f..913740b 100644 --- a/README.md +++ b/README.md @@ -10,12 +10,15 @@ The goal of miaDash is to provide a user-friendly interface to import, manipulate, analyse and visualise TreeSummarizedExperiment objects. ## Usage + miaDash is available online at [this address](iseebug-iseebug.2.rahtiapp.fi/). While suitable for small and medium datasets, the online version may slow down -when larger datasets are analysed (< 1000 features). In this case, the app can -be installed and run locally. Either way, the app also provides functionality to subset and agglomerate the data. +when larger datasets are analysed (> 1000 features). In this case, the app can +be installed and run locally. Either way, functionality to subset and +agglomerate the data is also provided in the app. ## Installation instructions + The devel version of miaDash can be installed from GitHub as follows: ``` @@ -23,6 +26,7 @@ remotes::install_github("RiboRings/miaDash") ``` ## Example + The basic functionality of miaDash can be explored as follows: ``` @@ -37,6 +41,7 @@ if (interactive()) { ``` ## Code of Conduct + Please note that the miaDash project is released with a [Contributor Code of Conduct](https://bioconductor.org/about/code-of-conduct/). By contributing to this project, you agree to abide by its terms. Contributions @@ -45,6 +50,7 @@ contributor guidelines of the miaverse [here](https://github.com/microbiome/mia/blob/devel/CONTRIBUTING.md). ## Acknowledgements + miaDash results from the joint effort of the larger R/Bioconductor community. In particular, this software mainly depends on the following packages: diff --git a/vignettes/miaDash.Rmd b/vignettes/miaDash.Rmd index 3ecd8e6..1f7743c 100644 --- a/vignettes/miaDash.Rmd +++ b/vignettes/miaDash.Rmd @@ -29,36 +29,90 @@ knitr::opts_chunk$set( ) ``` +```{r vignetteSetup, echo=FALSE, message=FALSE, warning=FALSE} +## Bib setup +library(RefManageR) + +## Write bibliography information +bib <- c( + R = citation(), + mia = citation("mia")[1], + iSEEtree = citation("iSEEtree")[1], + iSEE = citation("iSEE")[1], + TreeSummarizedExperiment = citation("TreeSummarizedExperiment")[1], + shiny = citation("shiny")[1] +) +``` + # Introduction -The Microbiome Analysis Dashboard (miaDash) aims to make microbiome analysis -accessible to anyone, with or without programming skills. +This notebook provides a practical introduction to the Microbiome Analysis +Dashboard (miaDash), an interactive app to analyse and explore microbiome data. +Feel free to try it online at +[this address](https://iseebug-iseebug.2.rahtiapp.fi/) with your data or one of +the ready-to-use example datasets. Here, its usage and functionality are +described in more detail. ## Motivation -## Interface +Most of the tools available for microbiome data analysis require some knowledge +of programming. This represents a burden for practitioners more interested +in getting results than learning how to program. To this end, miaDash aims to +make microbiome analysis accessible to anyone who needs it, with or without any +computational skills. + +As a word of caution, while the app removes the burden of programming, it is +still critical to understand the nature of microbiome data and how it can be +analysed. Such knowledge can be acquired from the online book [Orchestrating +Microbiome Analysis](https://microbiome.github.io/OMA/) (OMA) and several other +independent resources. The following section presents what is currently possible +in the app. -The interface provides tools to: +## Interface -- import from datasets from several file types or practice with a ready-made - mia dataset -- manipulate objects as subsetting, agglomeration and transformation -- estimate alpha and beta diversity -- visualise different aspects with iSEEtree +The interface is divided into five tabs that reflect the steps of a typical +microbiome analysis pipeline. First, the dataset of interest can be uploaded +through the Import tab, where several data types and file formats are supported. +Alternatively, one of the available example datasets can be used for practice. +Second, a set of operations can be applied to the dataset through the +Manipulate tab, which include methods for subsetting features by prevalence, +agglomerating by taxonomic level and transforming assays. Third, the dataset +can be analysed through the Estimate tab, which provide common techniques to +quantify alpha and beta diversity. Finally, results can be explored through the +Visualise tab, where an interactive explorer can be launched with a customisable +set of panels that illustrate different aspects of the data. # Tutorial +The app can be used online or locally, depending on resource availability and +size of the dataset to analyse. In general, the online version is freely +available, so that data of any type can be tested there. However, running the +app locally might be a better option for larger datasets (> 1000 features). In +this case, you may also consider subsetting and/or agglomerating the data. + ## Installation +If you decided to run the app locally, make sure to have R installed in your +machine and execute the following command: + ```{r install, eval=FALSE} +# Install from GitHub remotes::install_github("RiboRings/miaDash") ``` +Once the package is successfully installed, you should have access to the +development version of miaDash. + ## Example +This section shows how to get started with miaDash. If you are using it locally, +run the next code chunk to launch the app. Otherwise, you can skip it. + ```{r start, message=FALSE, warning=FALSE} +# Import miaDash library(miaDash) +# Instantiate app app <- miaDash() # Launch miaDash @@ -71,10 +125,31 @@ if (interactive()) { SCREENSHOT <- function(x, ...) knitr::include_graphics(x) ``` -```{r screenplot, echo=FALSE, out.width="100%"} -SCREENSHOT("screenshots/get_started.png", delay = 20) +As described in Section [1.2](#interface), The dashboard consists of five +different windows with tools to import, manipulate, analyse and visualise +the dataset of choice. After launching the app, it appears as follows: + +```{r screenplot1, echo=FALSE, out.width="100%"} +SCREENSHOT("screenshots/dashboard.png", delay = 20) ``` +At first, the variety of options might feel intimidating, so you can click on +the question mark on the top right to receive a short tour of the windows +available in the app. + +Once the dataset was imported and analysed according to your objective, you can +choose which visualisations to use from the Visualise window and press the +button "Launch iSEEtree" to create and customise the plots. After adjusting the +parameters of the different panels, the app might look something like this: + +```{r screenplot2, echo=FALSE, out.width="100%"} +SCREENSHOT("screenshots/iSEEtree.png", delay = 20) +``` + +As before, you can click on the question mark on the top right to receive a tour +of the panels and their parameters. The best way to get familiar with the +interface is to experiment with the parameters below each panel. + # Resources ## Citation @@ -89,14 +164,37 @@ citation("miaDash") ## Background Knowledge +miaDash originates from the joint effort of the R/Bioconductor community. It is +mainly based on the following software: + +- R `r Citep(bib[["R"]])`, statistical programming language +- `r Biocpkg("mia")` `r Citep(bib[["mia"]])`, framework for microbiome data analysis +- `r Biocpkg("iSEEtree")` `r Citep(bib[["iSEEtree"]])`, TreeSummarizedExperiment interactive explorer +- `r Biocpkg("iSEE")` `r Citep(bib[["iSEE"]])`, SummarizedExperiment interactive explorer +- `r Biocpkg("TreeSummarizedExperiment")` `r Citep(bib[["TreeSummarizedExperiment"]])`, S4 container for hierarchical data +- `r CRANpkg("shiny")` `r Citep(bib[["shiny"]])`, web app development in R + ## Help +You can reach us by one of the communication channels listed +[here](https://microbiome.github.io/OMA/docs/devel/pages/support.html). We are +happy to receive questions, suggestions as well as contributions. For the last +point, check the +[contributor guidelines](https://microbiome.github.io/mia/CONTRIBUTING.html). + # Reproducibility R session information: ```{r reproduce, echo=FALSE} -## Session info +# Session info options(width = 120) sessionInfo() ``` + +# References + +```{r vignetteBiblio, results="asis", echo=FALSE, warning=FALSE, message=FALSE} +# Print bibliography +PrintBibliography(bib, .opts = list(hyperlink = "to.doc", style = "html")) +``` \ No newline at end of file diff --git a/vignettes/screenshots/get_started.png b/vignettes/screenshots/dashboard.png similarity index 100% rename from vignettes/screenshots/get_started.png rename to vignettes/screenshots/dashboard.png diff --git a/vignettes/screenshots/iSEEtree.png b/vignettes/screenshots/iSEEtree.png new file mode 100644 index 0000000000000000000000000000000000000000..57f9cef7331f507e22265055288a3dcbf38859cf GIT binary patch literal 1026330 zcmeFZXH-<#x&;adN)Vxupb|wyVu2tT3PAzMIfnwtl5;E&5J8Y2IY-GkQ$#_6l5@^T 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b/Dockerfile index b941bef..577ab35 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,6 +1,5 @@ FROM bioconductor/bioconductor_docker:devel -MAINTAINER giulio.benedetti@utu.fi LABEL authors="giulio.benedetti@utu.fi" \ description="Docker image containing the miaDash package in a bioconductor/bioconductor_docker:devel container." diff --git a/inst/Dockerfile b/inst/Dockerfile index 3f9e226..4222e26 100644 --- a/inst/Dockerfile +++ b/inst/Dockerfile @@ -1,6 +1,5 @@ FROM ghcr.io/riborings/iseebug:devel -MAINTAINER giulio.benedetti@utu.fi LABEL authors="giulio.benedetti@utu.fi" \ description="Docker image containing the miaDash package."