DESeq2 with baseline correction for gene expression differences
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R1337 • 0
@09efc7cb
Last seen 3 months ago
Switzerland

Dear Community,

I have problably a relatively simple question, but I am quite new to DESeq2 and unfortunately couldn't find an answer to my question. I have the following dataset:

• Sample /Genotype / Injury / Condition
• 1 / WT / NO / WT_NO
• 2 / WT / YES / WT_YES
• 3 / KO / NO / KO_NO
• 4 / KO / YES. / KO_YES
• List item

...

I followed the guidelines for DESeq2 and could create a dds file

 dds <- DESeqDataSetFromMatrix(countData = rawCountTable,
colData = sampleInfo,
design = ~  Condition)


and then could extract the groups I would like to compare with

KO_YES_vs_KO_NO <- results(dds2, contrast=c("Condition", "KO_YES", "KO_NO") , independentFiltering=TRUE, alpha=0.05, pAdjustMethod="BH", parallel=TRUE)


However, the last comparison I would like to do is between the injury groups so WT_YES to KO_YES. For this I need a baseline correction (WT_NO and KO_NO). I am not sure how to add it into the DESeq command and unfortunately couldn't find anything to address this issue. I hope someone can help!

DESeq2 edgeR Transcriptomics • 299 views
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@mikelove
Last seen 1 day ago
United States

If you want to test the ratio of ratios, this would be an interaction term between two factor variables, see the vignette section and a number of support site posts on "ratio of ratios".

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Thank you Michael for your response! I managed to use ratio of ratios and updated my code like the following

dds <- DESeqDataSetFromMatrix(countData = rawCountTable3,
colData = sampleInfo3,
design = ~Genotype + Injury + Genotype:Injury)


If I run then

resultsNames(dds)


[1] "Intercept"               "Genotype_WT_vs_KO"      "Injury_Injury_vs_Ctrl"   "GenotypeWT.InjuryInjury"


I am not sure which of these to combine for my results command

results(dds, contrast=list("xxx", "yyy"))


( I want to. compare ratios of KO Injury (normalized to KO Ctrl) to WT injury (normalized to WT Ctrl).

Thank you!

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It is just the interaction term that is the ratio of ratios. Use results(..., name=""). But first read over the vignette note on factor levels (you have KO as the reference and WT as the effect, which is backwards).

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Great thank you!

I have updated the levels now I get as a result from resultsNames(dds)

[1] "Intercept"                "Genotype_KO_vs_WT"       "InjuryInjury_vs_Ctrl"    "GenotypeKO.InjuryInjury"



and then I simply run:

res <- results(dds, name = "Intercept")


...and "res" represents then the fold changes and p values for normalized KO injury / normalized WT injury?

Thank you!

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hi, no this is really off you are testing the intercept not the interaction, I'd recommend working with a statistician by the way. I can't provide statistical consultation here, due to limits on my time, I have to focus on software related issues only.