logfold shrinkage DESeq2
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sherajilir • 0
@sherajilir-18567
Last seen 2.6 years ago

Hi everyone,

I Did DESseq2 differential expression analysis for 180 samples from TCGA using HTSEQ raw counts. After following all the steps and normalizing for two factors i got the expressed data with lof2FC, pval and padj. Then i did log-fold shrinkage using the apeglm package and im getting differentialy-expressed genes with significant p-values but very small logfold changes, for example 0.0006, which should be the result of many samples i think. When i make a volcano plot i see genes overlapping at the center of it, something that does not happen when differential expression without log-fold shrinkage is done. Is there any statistical criteria for selecting those genes, for example, starting from log2FC 0.2, or 0.5? I know you can chose for highly-expressed genes, but my focus is enzymes which do not show a lot of change.

 

Thank You

deseq2 • 626 views
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@mikelove
Last seen 34 minutes ago
United States

The lfcThreshold (which can be specified in results or in lfcShrink) is up to you, depending on what you feel is a biologically relevant LFC. You might look at the MA plot of the shrunken LFC and decide based on that distribution.

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sherajilir • 0
@sherajilir-18567
Last seen 2.6 years ago

Thank you Michael for the quick reply.

Actually the shrinked lfc MA plot is something like this

https://www.dropbox.com/s/hun8s44twzxw3g2/Shrinked%20lfc%20plot.tiff?dl=0

But i think i got the answer.

 

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