DESeq2 - Plot Nr. Genes vs Variance explained in PCA
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@andrebolerbarros-16788
Last seen 9 days ago
Portugal

Hey everyone,

I know the plotPCA function from DESeq2uses, by default, only the 500 most variable genes. I was wondering if it makes sense, or if anyone has done, a plot where we check the explained variance by PC1 and PC2 as a function of the number of genes considered.

Something like this: enter image description here

Where X is the Number of Genes considered and Y is the sum of variance explained by the first 2 PC's.

Thank you in advance!

DESeq2 • 328 views
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@mikelove
Last seen 13 hours ago
United States

One thing a little tricky about this analysis is that the denominator is changing (total variance in the top 'N' genes).

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Indeed, we are constantly changing the amount of variance in our data. But, this was the best way to get a better "grasp" on what would be the right amount of genes that, at that level of variance, a 2 PC PCA plot could better explain that variance - does this make sense? Would you do it in a different way?

I was maybe thinking about including more PC's (up to 3 or 4), which we can then plot in pairwise fashion (PC1 vs PC2, PC1 vs PC3, ...). What do you think?

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I mean exploring your data in many ways is always a good idea (here I don't mean doing a bunch of null hypothesis testing, but EDA), can't go wrong.

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