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134 lines
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HTML
134 lines
6.4 KiB
HTML
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<title>Methods | cellxgene</title>
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<meta name="description" content="An interactive explorer for single-cell transcriptomics data" />
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<div class="wrapper">
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<header>
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<img src="/cellxgene/cellxgene-logo.png" alt="cellxgene" />
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<p>An interactive explorer for single-cell transcriptomics data</p>
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<p>
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<a href="/cellxgene/" class="btn">Quick start</a><br>
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<a href="/cellxgene/posts/install" class="btn">Installation</a><br>
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<a href="/cellxgene/posts/gallery" class="btn">Gallery</a><br>
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<a href="https://cellxgene.cziscience.com/" class="btn">Cellxgene data portal</a><br>
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<a href="/cellxgene/posts/demo-data" class="btn">Demo datasets</a><br>
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<a href="/cellxgene/posts/prepare" class="btn">Preparing your data</a><br>
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<a href="/cellxgene/posts/launch" class="btn">Launching cellxgene</a><br>
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<a href="/cellxgene/posts/hosted" class="btn">Hosting cellxgene</a><br>
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<a href="/cellxgene/posts/annotations" class="btn">Annotating data</a><br>
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<a href="/cellxgene/posts/methods" class="btn"><b>Methods</b></a><br>
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<a href="/cellxgene/posts/troubleshooting" class="btn">Troubleshooting</a><br>
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<a href="/cellxgene/posts/roadmap" class="btn">Roadmap</a><br>
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<a href="/cellxgene/posts/contribute" class="btn">Contributing (ideas or code)</a><br>
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<a href="/cellxgene/posts/contact" class="btn">Contact & finding help</a><br>
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<a href="https://github.com/chanzuckerberg/cellxgene" class="btn" target="_blank">Code</a>
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</p>
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</header>
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<section>
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<h1 id="methods">Methods</h1>
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<h2 id="data-structure-anndata-fields-used-for-visualization">Data structure: <em>anndata</em> fields used for visualization</h2>
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<h3 id="expression-data">Expression data</h3>
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<p>Gene expression values are pulled from <code class="language-plaintext highlighter-rouge">anndata.X</code>. These feed into the histograms, scatterplot, colorscale, and differential expression calculations. We’re <a href="https://github.com/chanzuckerberg/cellxgene/issues/689">working on ways</a> to incorporate <code class="language-plaintext highlighter-rouge">anndata.raw</code> and other <code class="language-plaintext highlighter-rouge">anndata.layers</code>!</p>
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<h3 id="metadata">Metadata</h3>
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<p>Categorical (e.g., cluster labels) and continuous (e.g., pseudotime) metadata are pulled from <code class="language-plaintext highlighter-rouge">anndata.obs</code>. Any column added here will be available for visualization in cellxgene. You can also <a href="annotations">create new categorical annotations</a> within the application.</p>
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<h3 id="embeddings">Embeddings</h3>
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<p>cellxgene looks for embeddings (e.g., tSNE, UMAP, PCA, spatial coordinates) in <code class="language-plaintext highlighter-rouge">anndata.obsm</code>. These fields must follow the scanpy convention of starting with <code class="language-plaintext highlighter-rouge">X_</code>, e.g., <code class="language-plaintext highlighter-rouge">anndata.obsm['X_umap']</code>. If an embedding has more than two components, the first two will be used for visualization.</p>
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<h2 id="differential-expression">Differential expression</h2>
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<p>We’re actively working on how to improve differential expression within the app.
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<strong>N.B.: the <a href="https://github.com/chanzuckerberg/cellxgene/blob/main/server/app/scanpy_engine/diffexp.py#L40">current implementation</a> assumes normally distributed values on a linear scale.</strong></p>
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<p>Currently, we use a <a href="https://en.wikipedia.org/wiki/Welch%27s_t-test">Welch’s <em>t</em>-test</a>, which assumes that the two populations are each normally distributed, but may have unequal variance. We use a two-sided t-test against the null hypothesis that the two populations have <strong>equal</strong> means. P-values are adjusted with the <a href="https://en.wikipedia.org/wiki/Bonferroni_correction">Bonferroni corrrection</a>.</p>
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<p>To help avoid spurious results, we use the log fold change to filter genes, retaining those where <code class="language-plaintext highlighter-rouge">|log2( mean(set1) / mean(set2) )| > 0.01</code>; this threshold can be configured with the <a href="launch"><code class="language-plaintext highlighter-rouge">--diffexp-lfc-cutoff</code></a> command. We then sort genes by their associated <code class="language-plaintext highlighter-rouge">|t value|</code> and return the top 15 genes.</p>
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</section>
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<footer>
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<p>This project is maintained by <a href="https://github.com/chanzuckerberg">chanzuckerberg</a></p>
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