p-value and log fold change

[Bidfudge]

Hi everyone,

I was using DEseq2 to analyse my data from RNAsequencing.
Basically, i have 2 conditions and i would like to evaluate which gene are differentially expressed between these both conditions.
So i performed a DEseq2 analysis with my aligned data, and i used a Bonferroni correction for the multiple testing.
What i don't understand is that i have some differentially expressed genes in my experiment, (padj<0.05), but when i looked for the fold change of transformed data (with the assay(...) function of DEseq2), i find some DE gene which have for example just 1.00 in fold change.
So i was wondering how a gene can be considerated as DE even if there is not fold change between the both condition.

Maybe i miss something, this is my first analyse of RNAseq data

Thanks you and also all the contributors that provides some powerful advices in this forum =)

[dpryan]

That's the log2 fold-change, so a value of 1 is a 2x difference.

BTW, I wouldn't recommend using a bonferroni adjustment, it's going to be overly conservative. The default p-value adjustment method (BH) is more appropriate.

[Bidfudge]

Oh damn, i'm stupid ))

Thanks for the help, i was wrong for the correction, i used BH

thks again for the help

[wdecoster]

Log fold change makes more sense than just fold change because:
-overexpression and underexpression of the same extent have the same value
-the scale is correct

In fold change, everything that's underexpressed get's squeezed between 0 and 1, with everything overexpressed from 1 to Inf...