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<scheme description="The workflow shows the use of alignment of two data sets. It uses canonical correlation analysis to de-correlate expression with batch effects. The effect of the alignment is visible in t-SNE plot and is evaluated through shared information content between batch IDs and clusters." title="Data set alignment" version="2.0">
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		<text font-family="Helvetica" font-size="16" id="0" rect="(-90.0, -19.0, 386.0, 170.0)" type="text/html">&lt;b&gt;Data Set Alignment&lt;/b&gt;
&lt;br/&gt;
&lt;br/&gt;
The workflow loads a merged data set from Kang et al. (2018) containing 1,000 controls and stimulated cells and 1,500 highly variable genes and shows how to remove batch effects. Controls and stimulated cells are well-separated in the original data set. Alignment based on canonical correlation analysis (CCA) reduces the separation between these two sources.</text>
		<text font-family="Helvetica" font-size="14" id="1" rect="(-75.0, 178.0, 136.0, 87.0)" type="text/plain">Loads the data where the batches are marked with Source ID column (CTRL vs. STIM).</text>
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		<text font-family="Helvetica" font-size="14" id="3" rect="(22.0, 564.0, 150.0, 54.0)" type="text/plain">Aligns the data sets using canonical correlation analysis.</text>
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		<text font-family="Helvetica" font-size="14" id="5" rect="(480.0, 317.0, 270.0, 68.0)" type="text/plain">Clusters in original data sets are enriched with cells from one of the batches. Alignment substantially reduces this correlation.</text>
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		<text font-family="Helvetica" font-size="14" id="8" rect="(570.0, 170.0, 229.0, 83.0)" type="text/plain">Scores the correlation between the clusters and data experiment type (data source). Information gain is high (&gt; 0.5), hence clusters correspond to the data source.</text>
		<text font-family="Helvetica" font-size="14" id="9" rect="(572.0, 454.0, 169.0, 82.0)" type="text/plain">Clusters provide low information about the data source (information gain &lt; 0.1) after alignment.</text>
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		<text font-family="Helvetica" font-size="14" id="12" rect="(459.0, 623.0, 234.0, 53.0)" type="text/plain">Compare with t-SNE on original data. After alignment, the cells from different sources are well mixed.</text>
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