Fold change calculation in Diffbind vs. DESEQ2?
Entering edit mode
marcusn • 0
Last seen 6 weeks ago

Hello :)

I have a RNA-seq dataset and a ChIP-Seq dataset and I have ran a differential binding analysis and differential expression analysis, both using DESEQ2.

For the RNA-seq I have just followed a standard and the resulting tsv has the following columns:


For the ChIP-Seq I have used diffbind to perform the deseq analysis, and extracted the deseq2 object using and and now it has the following columns:

...., Conc, Conc_x,Conc_y, Fold, p-valule, FDR

When I plot both the fold changes (log2FoldChange vs Fold) in a scatterplot it does not appear that these are calculated equally. The RNA DESEQ fold changes appear to be evenly disributed over a range (-4 to -4), with alot of genes showing no major changes. The diffbind DESEQ2 analysis however yield a strange scatterplot pattern where there are no significant samples with a fold change between 1 and -1.

My question is if these DESEQ2 fold changes are calculated equally? If not how should I go about applying the same log2foldchange formula to both datasets?

I am very happy to clarify should something be unclear :)



DiffBind ChIPSeqData DESeq2 • 215 views
Entering edit mode
Last seen 1 day ago
United States

There was a recent DiffBind question on the support site that noticed the same thing, try searching recent DiffBind posts.


Login before adding your answer.

Traffic: 438 users visited in the last hour
Help About
Access RSS

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6