DESeq2 analysis using two featureCounts generated from different studies
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5 months ago
abedkurdi10 ▴ 190

Hello everyone,

I have a question related to DESeq2, just to make sure I am not missing anything. We have RNA-seq data and we generated the count matrix using featureCounts. Then, during our analysis and research, we found interesting data available online and wanted to use it and __compare our data to the data found__ (perform differential expression analysis).

I was checking the DESeq2 vignette and my understanding is that I should include in the __colData__ an additional column, and then include it in the formula, for instance, ~source + condition. This will allow me to compare the conditions while also accounting for the source. Am I right?

Thank you in advance.

RNA-seq DESeq2 • 669 views
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5 months ago
Asaf 10k

Yes, you are correct. However, there are several things you should consider:

  1. For DESeq2 to be able to normalize both datasets together there should be some overlap of genes expressed.
  2. You would probably want to include the interaction factor source:condition in your formula. This factor will indicate if the two sources agree on the gene expression changes due to the condition (if this factor effect is low), or the two sources disagree (high effect with a strong p-value)
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5 months ago
petebio ▴ 100

This might not necessarily be the best way to do an RNA-Seq analysis. RNA-Seq is famously sensitive to all sorts of factors like who did the experiment, how the cells were treated etc. Using data from an entirely different lab and entirely different experiment might be too much of a confounding issue.

The formula that you have would be how we would normally account for batch effects - which I guess would fit here. But given how different the data is likely to be I would not really trust the results of this analysis.

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5 months ago

Comparing samples between labs is a bad idea. Better to generate gene lists from one study from one lab, and gene lists from another study from another lab, then compare the gene lists.

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What do you mean by gene lists?

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