Hi,

We have two cohorts, cases and controls and a set of covariates for both of them ( center, library.prep.date, age, rna.rin.score, sex ).
Center and library.prep.date are collinear with the status (all the cases were collected in London while the controls
were collected in 4 different centers worldwide) so I used the first principal component of these two covariates and ran DESeq2 using this design:
~ PC1 + age + rna.rin.score + sex + status

Unfortunately it looks like the batch effect is too strong and I have ~16K genes with adjP<0.05
One question: is the fold-change still reliable  (So that I can use it as rank for GSEA analysie for example) ?
Now, although the differential expression might be hampered by the study design and I don’t know if I can use these results (what do you think?)
the main problem is the following:

I have based all the analyses for my PhD thesis and the manuscript I am preparing using DESeq.
The pipeline is based on co-expression clustering (WGCNA), diffco-ex between cases and controls and GWAS hits enrichment in these clusters.

For the pre-processing of these analyses I’ve first obtained the VST data and then adjusted these for the covariates using a linear model. Then I used the residuals for the analyses:

> vsd <- varianceStabilizingTransformation(dds, blind=TRUE)
> vstMat <- assay(vsd)
> lm=lm(vstMat ~ as.factor(info$library.prep.date) + as.numeric(info$age) + as.factor(info$sex) + as.numeric(info$rna.rin.score) + as.factor(info$center))
> data = residuals(lm)

The main question is that we are not sure if this pre-processing is correct, does the linear model work here for this purpose on VST data ?
(The doubt came by the fact that a fold-change for one gene of interest suggested it was strongly up-regulated in cases, but when boxplotting the residuals from the linear model adjusted for all the covariates you don’t see any difference at all…)

Thank you very much in advance

Looking forward to you reply

Best
- Francesco

Francesco Pesce MD
Early Stage Researcher (Marie Curie Fellow)
National Heart & Lung Institute
Imperial College London

Mobile: 0044 (0)7928 341136
Email: f.pesce@imperial.ac.uk<mailto:f.pesce@imperial.ac.uk>
Skype: francpesce

Please note: The content of this e-mail (including any attachment) contain confidential information and may be protected by law as a legally privileged document and copyright work. Its content should not be disclosed and it should not be given or copied to anyone other than the person(s) named or referenced above. If you have received this mail in error, please contact the sender immediately on the telephone or fax numbers above and then delete it (including any attachment) from your system. Thank you.

	[[alternative HTML version deleted]]

