Hi Andrew,
Thanks very much for your response. As you say, reducing the number is not appropriate and I would expect those genes to be differentially methylated using all probes if they truly were (without the reduction), is that correct? Thanks
IOM
Hi,
Thanks for reading, I would like to ask you for your opinion. I would like perform a methylation analysis comparing two groups of samples with a determined number of probes/genes, not using all the probes available in the array (this gene list comes from a literature search). My questions are:
Any help will be much appreciated. Thanks
IOM
Assuming that you've applied a normalisation process with Minfi, and you have a resulting GenomicRatioSet class object, you can get the annotation using:
norm_data_f <- norm_data_f %>% addSnpInfo
norm_data_f <- norm_data_f %>% dropLociWithSnps(., snps = c("SBE","CpG","Probe"), maf = 0.05)
annotation <- norm_data_f %>% getAnnotation %>% as.data.frame
Which gives you a full set of annotation for your probes, prior to modelling with Limma. The GenomicRatioSet is also a subsettable S4 class, so you can use the annotation to provide sensible filtering. Minfi provides a nice helper function dropLociWithSnps for probe level filtering.
Generally speaking, I wouldn't cherry pick genes to test, I'd run the contrast across all probes passing your probe level filters. Pre-selecting genes to test means that you reduce the total number of tests, and the resulting FDR is more lenient.
Hi Andrew,
Thanks very much for your response. As you say, reducing the number is not appropriate and I would expect those genes to be differentially methylated using all probes if they truly were (without the reduction), is that correct? Thanks
IOM
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