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Old 07-25-2016, 01:55 AM   #1
Junior Member
Location: France

Join Date: Jun 2016
Posts: 6
Default p-value and log fold change

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 =)
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Old 07-25-2016, 02:15 AM   #2
Devon Ryan
Location: Freiburg, Germany

Join Date: Jul 2011
Posts: 3,480

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.
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Old 07-25-2016, 02:32 AM   #3
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Location: France

Join Date: Jun 2016
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Oh damn, i'm stupid ))

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

thks again for the help
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Old 07-25-2016, 03:00 AM   #4
Location: Antwerp, Belgium

Join Date: Oct 2015
Posts: 97

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...
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