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Finished MOFA chapter
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@oliviaAB
oliviaAB committed Jan 24, 2024
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2 changes: 1 addition & 1 deletion _targets.R
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Expand Up @@ -523,7 +523,7 @@ list(
),
training_options = list(seed = 43)
),
only_common_samples = TRUE
only_common_samples = FALSE
)
),

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4 changes: 2 additions & 2 deletions _targets/meta/meta
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Expand Up @@ -52,8 +52,8 @@ mo_set_complete|stem|d79178dd6687be97|d76a85ef218e0cef|952f06b34b51e191|17398688
mo_set_de|stem|2b7e2ace37c0bed5|50f81c565a9dc6aa|1d4929f8d72b5561|1698094396||t19739.0034448046s|fa7930e7b638c680|37442539|rds|local|vector|||0.167|rnaseq dataset 1594 feature IDs missing from df dataframe.|
mo_set_transformed|stem|28334a82bdfebaa7|1a49152e06c5222d|6f732476e2857317|385723480||t19739.9580970037s|5c19986154657d81|57773059|rds|local|vector|||0.252||
mo_set_with_names|stem|e64ebcd89ddb70bd|b88cddcfa5d2a267|6eebd2f68cb73320|-1640374052||t19738.0568285842s|593ace30823e21f2|36753195|rds|local|vector|||0.114||
mofa_input|stem|55da511de7664cd8|a8548080dfc5818e|b1ff01b4e620143d|1284502458||t19746.154401993s|e22ca446e6bece21|837460|rds|local|vector|||0.324|Dataset snps is to be modelled with a poisson likelihood, but is not integer. Transforming to integer.|
mofa_trained|stem|b38f267e60c1989a|ec971dccb1086e60|91cc7bf157eacf61|1854191013||t19746.1563374787s|29bcdeb5af24197c|966299|rds|local|vector|||166.175|No output filename provided. Using tmpRtmpHWxlYdmofa_20240124164221.hdf5 to store the trained model.. Factors 1 are strongly correlated with the total number of expressed features for at least one of your omics. Such factors appear when there are differences in the total levels between your samples, sometimes because of poor normalisation in the preprocessing steps.|
mofa_input|stem|4d8e1c14434288d1|3d5db0316055019b|b1ff01b4e620143d|1284502458||t19746.8899165855s|4110beb5e0ca03cd|877459|rds|local|vector|||0.201|Dataset snps is to be modelled with a poisson likelihood, but is not integer. Transforming to integer.|
mofa_trained|stem|f523901c69cc8163|ec971dccb1086e60|dec5748f700e63fc|1854191013||t19746.8912693121s|b341cd3de1b49e2f|1004645|rds|local|vector|||116.597|No output filename provided. Using tmpRtmpaM7XWKmofa_20240125102128.hdf5 to store the trained model.. Factors 1 are strongly correlated with the total number of expressed features for at least one of your omics. Such factors appear when there are differences in the total levels between your samples, sometimes because of poor normalisation in the preprocessing steps.|
omicspls_input|stem|488cc165105ef587|5103f8e1eb31dfb4|3fe933389d7e1821|1468063698||t19746.0144579806s|8dac9e868840a7ff|957717|rds|local|vector|||0.009||
pca_mats_list|pattern|c831051151e4add2|72b302a65c0920ed||1078442447||||12164806|rds|local|list||pca_mats_list_302d7473*pca_mats_list_84d36937*pca_mats_list_64d37e6c|0.09||
pca_mats_list_302d7473|branch|e839c68784be56c5|72b302a65c0920ed|0f98021e133aac1d|-46563577||t19739.9581108254s|1b793e6da03f6fbf|1616638|rds|local|list|pca_mats_list||0.072||
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11 changes: 8 additions & 3 deletions docs/data_import.html
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Expand Up @@ -228,6 +228,11 @@ <h1 class="quarto-secondary-nav-title"><span class="chapter-number">3</span>&nbs
<div class="sidebar-item-container">
<a href="./so2pls.html" class="sidebar-item-text sidebar-link"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Integration with sO2PLS</span></a>
</div>
</li>
<li class="sidebar-item">
<div class="sidebar-item-container">
<a href="./mofa.html" class="sidebar-item-text sidebar-link"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Integration with MOFA</span></a>
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Expand All @@ -241,7 +246,7 @@ <h1 class="quarto-secondary-nav-title"><span class="chapter-number">3</span>&nbs
<ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">
<li class="sidebar-item">
<div class="sidebar-item-container">
<a href="./diablo.html" class="sidebar-item-text sidebar-link"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Integration with DIABLO</span></a>
<a href="./diablo.html" class="sidebar-item-text sidebar-link"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Integration with DIABLO</span></a>
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Expand All @@ -256,7 +261,7 @@ <h1 class="quarto-secondary-nav-title"><span class="chapter-number">3</span>&nbs
<ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">
<li class="sidebar-item">
<div class="sidebar-item-container">
<a href="./interpretation.html" class="sidebar-item-text sidebar-link"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Interpreting the integration results</span></a>
<a href="./interpretation.html" class="sidebar-item-text sidebar-link"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Interpreting the integration results</span></a>
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<p>The created target, called <code>dataset_file_geno</code>, takes as value the path to the file:</p>
<div class="cell">
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r code-with-copy"><code class="sourceCode R"><span><span class="fu"><a href="https://docs.ropensci.org/targets/reference/tar_read.html">tar_read</a></span><span class="op">(</span><span class="va">dataset_file_geno</span><span class="op">)</span></span>
<span><span class="co">#&gt; [1] "/powerplant/workspace/hrpoab/RENV_CACHE/v5/R-4.2/x86_64-pc-linux-gnu/moiraine/0.0.0.9000/ea944811306c200792f0808f5fa53cec/moiraine/extdata/genomics_dataset.csv"</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<span><span class="co">#&gt; [1] "/powerplant/workspace/hrpoab/RENV_CACHE/v5/R-4.2/x86_64-pc-linux-gnu/moiraine/0.0.0.9000/c5fcba1231fe0ad084ba7ffc17cfc3e0/moiraine/extdata/genomics_dataset.csv"</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<p>The next step is to import this dataset in R. We use the <code><a href="https://rdrr.io/pkg/moiraine/man/import_dataset_csv.html">import_dataset_csv()</a></code> function for that, rather than the <code><a href="https://readr.tidyverse.org/reference/read_delim.html">readr::read_csv()</a></code> or similar functions, as it ensures that the data is imported with the correct format for further use with the <code>moiraine</code> package. When importing a dataset, we need to specify the path to the file, as well as the name of the column in the csv file that contains the row names (through the <code>col_id</code> argument). In addition, we need to specify whether the features are represented in rows in the csv file, or in columns. This is done through the argument <code>features_as_rows</code>. For example, we can load the genomics dataset through:</p>
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