logFoldChange computed by EdgeR different from naive log2FCcomputed based on reads
Entering edit mode
2.5 years ago
ZheFrench ▴ 540

For example, for one gene:

logFC edgeR = 4

log2(mean reads condition A / mean reads condtition B ) = 3

For all genes, all the logFC computed from edgeR seems to be different ~ +1 from naive computation based on reads log2(mean Reads samples cond A / means Reads samples cond B).

It seems a huge difference, quite difficult to explain to a lambda user. Also curious to understand what could be the factor responsible for this kind of offset.

How can you explain that with edge R and glmfit ?

I'm doing something classical :

cm     <- makeContrasts(contrasts = comp,levels = dge$samples$group)

dge    <- estimateDisp(dge, de.design,robust=T)

fit.y  <- glmFit(dge, de.design)
lrt    <- glmLRT(fit.y,contrast = cm)
edgeR fold-change • 461 views

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