Changes in DESeq2 Version 1.20?
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hinkel2 • 0
@hinkel2-16914
Last seen 5.1 years ago

Hi all,
I'm working on RNAseq data set and use DESeq2 in order to find differentially expressed genes above a given log2FoldChange, say 2 (or -2 for downregulated genes), by simply using R to filter all results above 2 and below -2, respectiely. I performed this analysis according to manual and everything worked well two weeks ago.

Today I ran the script again with same parameters and same input, but I got different result, e.g. I found a higher number of upregulated genes compared to the run two weeks ago. When I check for given genes in my old and new results I can see that baseMean is still the same but log2FoldChangechanged.
I can also see that lcfSE was always below 1 in my two week-old results, but now its in above 1 in most cases.

I saw that a new version of DESeq2 was released some days ago.

Now my question: Was statistical computation of l2fc somehow altered? I can simply not figure out why my results differ... Looking forward to your answers!

Best regards
Andi

deseq2 • 575 views
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@mikelove
Last seen 2 hours ago
United States

I didn't see this because the 'deseq2' tag wasn't used.

Are you using a cluster? Likely what happened is that someone update the version of R and Bioconductor, switching you from a previous version to the current version.

The estimate of LFC that DESeq() and results() gives you hasn't changed since version 1.16 which was released in April 2017. So if you were using R/Bioconductor from October 2016, then you would have seen this change. This is typically what happened when people report something like you are describing. See here:

New function lfcShrink() in DESeq2

The estimate which lfcShrink() gives you depends on which method you use. It basically hasn't changed also since version 1.16, except that in the last release there were some big improvements made to the speed of apeglm, but the estimates themselves would be the same since the release of apeglm in October 2017.

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