Batch correction with uncertain biological variables
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@vedranfranke-7218
Last seen 3.5 years ago
Germany

I am currently trying to analyze a set of expression experiments from different tissues.

Some of the expression profiles originate from knockout experiments, for which we expect to cause trans-differentiation.

The experiments suffer from strong batch affects which are unknown, but fortunately, not perfectly confounded with biological variables of interest.

I have tried using sva to find the unknown batch effects - which works, however, I have a sense that the procedure might also be removing biological variance. 

Namely, the problem arises when specifying the mod matrix argument. If I specify the mod argument as WT - T1, WT - T2 ... KO - T1, KO - T2 ...; sva finds the batch effects, which results in samples clustering by their corresponding biological variables. However, there is a chance that some of the KO samples actually behave like WT samples - e.g. KO - T1 biologically becomes WT - T2, in which case sva actually removes the difference.

Is there a way to incorporate this uncertainty during sva modelling?

Additionally, I have found sva to be extremely sensitive to the exact samples which I use for estimating batch effects. Is there an easy way to assess the robustness of the bach effect estimation?

 

Best regards, 

 

Vedran

 

sva svaseq batch effect batch effects batch effect correction • 763 views
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