manuscript.ICIKendallTauMetabolomics/README.html at main · MoseleyBioinformaticsLab/manuscript.ICIKendallTauMetabolomics · GitHub

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<h2 id="sec:code-and-data-for-information-content-informed-kendall-tau-correlation-methodology-interpreting-missing-values-in-metabolomics-as-potentially-useful-information">Code and Data for Information-Content-Informed Kendall-tau Correlation Methodology: Interpreting Missing Values in Metabolomics as Potentially Useful Information</h2>
<p><a href = "https://doi.org/10.5281/zenodo.18625643"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.18625643.svg" alt="Zenodo Repository"></a></p>
<p><a href="https://doi.org/10.5281/zenodo.18625643"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.18625643.svg" alt="DOI" /></a></p>
<p>This repository contains the code and partial data for the manuscript:</p>
<p><strong>Information-Content-Informed Kendall-tau Correlation Methodology: Interpreting Missing Values in Metabolomics as Potentially Useful Information</strong>, R.M. Flight, P.S. Bhatt, and H.N.B. Moseley.</p>
<h2 id="sec:manuscripts">Manuscripts</h2>
<ul>
<li><a href="https://moseleybioinformaticslab.github.io/manuscript.ICIKendallTauMetabolomics/ici_kt_manuscript.html">Main Manuscript - HTML</a></li>
<li><a href="https://moseleybioinformaticslab.github.io/manuscript.ICIKendallTauMetabolomics/ici_kt_manuscript_mdpi.docx">Main Manuscript - Word</a></li>
<li><a href="https://moseleybioinformaticslab.github.io/manuscript.ICIKendallTauMetabolomics/supplemental_materials.html">Supplemental Materials - HTML</a></li>
<li><a href="https://moseleybioinformaticslab.github.io/manuscript.ICIKendallTauMetabolomics/supplemental_materials.docx">Supplemental Materials - Word</a></li>
</ul>
<h2 id="sec:grant-support">Grant Support</h2>
<p>This work was supported by the following grants:</p>
<ul>
<li>NSF 2020026 (PI Moseley);</li>
<li>NIH 1R03LM014928-01 (PI Moseley);</li>
<li>NSF ACI1626364 (Griffioen, Moseley);</li>
<li>P30 CA177558 (PI Evers) via the Markey Cancer Center Biostatistics and Bioinformatics Shared Resource Facility (MCC BB-SRF);</li>
<li>P20 GM121327 (PD St. Clair);</li>
<li>P42 ES007380 (PI Pennell) via the Data Management and Analysis Core (DMAC).</li>
</ul>
<h2 id="sec:license">License</h2>
<p>The contents of this work are licensed under a CC-BY license.
If you use any content, you must give attribution to this original work.</p>
<h2 id="sec:r-packages-needed">R Packages Needed</h2>
<p>The repository used R 4.4.1, and {renv} 1.0.10
For all of the other packages needed, see the file <code>renv.lock</code>.</p>
<p>To setup to be able to rerun everything here, you can clone the repo from <a href="https://github.com/MoseleyBioinformaticsLab/manuscript.ICIKendallTauMetabolomics">github</a> or download it from <a href="https://doi.org/10.5281/zenodo.18625643">Zenodo</a>:</p>
<pre><code># clone from github
git clone https://github.com/MoseleyBioinformaticsLab/manuscript.ICIKendallTauMetabolomics.git
</code></pre>
<pre><code># download from zenodo
wget 'https://zenodo.org/records/19112314/files/MoseleyBioinformaticsLab/manuscript.ICIKendallTauMetabolomics-v_0.3.zip?download=1' --output-document=manuscript.ICIKendallTauMetabolomics.zip
unzip manuscript.ICIKendallTauMetabolomics.zip
</code></pre>
<pre><code>cd manuscript.ICIKendallTauMetabolomics
</code></pre>
<p>Start an R session, and make sure <code>renv</code> is installed.</p>
<pre><code class="language-r"># make sure renv is installed
install.packages(&quot;renv&quot;)
# restore the packages
renv::restore()
</code></pre>
<p>The {ICIKendallTau} package on GitHub you want to use is the 1.2.16 release.
This is available on zenodo as well.</p>
<pre><code class="language-r">renv::install(&quot;moseleybioinformaticslab/ICIKendallTau@v_1.2.16&quot;)
</code></pre>
<p>Or:</p>
<pre><code>wget 'https://zenodo.org/records/18675151/files/MoseleyBioinformaticsLab/ICIKendallTau-v_1.2.16.zip?download=1' --output-document=ICIKendallTau-v_1.2.16.zip
unzip ICIKendallTau-v_1.2.16.zip
cd ICIKendallTau-v_1.2.16
</code></pre>
<p>Then start an R session from within the directory, and install it.</p>
<pre><code class="language-r">remotes::install_local()
</code></pre>
<h2 id="sec:obtaining-targets-cache-and-supporting-datasets">Obtaining targets Cache and Supporting Datasets</h2>
<p>To rerun the analyses, you will need at least the Metabolomics Workbench (MW) datasets and the compound annotations, all hosted on Zenodo.
We also include the instructions to download the original <code>targets</code> cache so you can avoid recomputing everything if you like.</p>
<pre><code># required
mkdir mwtab
cd mwtab
wget https://zenodo.org/records/19115655/files/mwbench.tgz?download=1 --output-document=mwbench.tgz
tar -xzf mwbench.tgz
cd ..

# required
mkdir predicted_annotations
cd predicted_annotations
wget https://zenodo.org/records/19115655/files/predicted_annotations.tgz?download=1 --output-document=predicted_annotations.tgz
tar -xzf predicted_annotations.tgz
cd ..

# optional, but suggested
# Note this is 26GB, it will take some time to download!
cd manuscript.ICIKendallTauMetabolomics
wget https://zenodo.org/records/19115655/files/icikt_metabolomics_targets.tgz?download=1 --output-document=icikt_metabolomics_targets.tgz
tar -xzf icikt_metabolomics_targets.tgz
cd ..
</code></pre>
<p>From within the manuscript project, you will want to link to the MW datasets and the annotations.</p>
<pre><code>cd manuscript.ICIKendallTauMetabolomics
ln -s mwtab path/to/mwtab
ln -s predicted_annotations path/to/predicted_annotations/annotations
</code></pre>
<p>Now you can start R, and hopefully nothing is outdated.</p>
<pre><code class="language-r">targets::tar_source(c(&quot;R&quot;, &quot;./packages.R&quot;))
tar_outdated()
</code></pre>
<h2 id="sec:rerunning">Rerunning</h2>
<p>This project consists of 91,669 targets for the analysis.
This is because I really wasn’t thinking when I designed it, and didn’t think to group the MW datasets into batches to be processed.
It made my life easier, but that is a <strong>lot</strong> of things, even though 61,637 are <code>NULL</code> objects that still have to be checked whenever you do anything involving the workflow beyond loading things.</p>
<h3 id="sec:manuscript-and-supplemental-materials">Manuscript and Supplemental Materials</h3>
<p>This is why the manuscript and supplemental materials <strong>are not</strong> actual targets of the workflow.
If you just want to check them, then you can do:</p>
<pre><code class="language-r">rmarkdown::render(&quot;docs/supplemental_materials.Rmd&quot;, output_format = &quot;rmarkdown::html_document&quot;, knit_root_dir = getwd())
rmarkdown::render(&quot;docs/ici_kt_manuscript.Rmd&quot;, output_format = &quot;rmarkdown::html_document&quot;, knit_root_dir = getwd())
</code></pre>
<h3 id="sec:everything-else">Everything Else</h3>
<p>You might want to uncomment at the top of the <code>_targets.R</code> file to use some multiprocessing, and watch your RAM useage.</p>
<pre><code class="language-r">targets::tar_make()
</code></pre>
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