Hi,
I am planning to preprocess 40 microarray series comprising of 1200 samples. For all these series, mRNAs were quantified using same platform "GPL570". I thought of using ComBat for batch effect correction prior to differential analysis. But, I don't know at which step that I need to use comBat.
Which is the correct procedure?
Background correction, Normalization , filtering the probes based on present and absent calls (panp package in R) and combat
or
Backgroung correction, Normalization, batch effect removal using combat and filtering the probes based on present and absent calls (panp package in R).
There is no defined method and Each paper follows different methodology. Please let me know.
Thanking you for your time.
1 answer
I was under the impression that due to the Bayesian nature of ComBat, it worked best with as much information re: distribution as possible, therefore should be done before filtering.
Side note: filtering by variance seems to be a popular alternative to detection calls. See bioconductor package "genefilter".
I like it because I found that panp doesn't play nicely with the updated CDFs available at brainarray.
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brendan.innes •
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