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For a given gene, we select the probe with the maximum standard deviation across all beta values. Then we discard any probes with a standard deviation below a specified cutoff. The default cutoff is .2, but it can be tuned based on the desired output file size.
Correlation with
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expression data
We start by filtering the methylation and expression data even further. We make a list of genes and individuals appearing in each file, and keep only the beta values for genes and individuals that appear in both. This leaves us with multiple methylation probes per gene, and a single measured expression level per gene.
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- *.meth.by_mean.data : calculating the mean signal values among each gene
- *.meth.by_min_clinexpr_corr.data : picking the probe with the min correlation with clinical mRNAseq data for each gene
- *.meth.by_min_exprclin_corr.data : picking the probe with the min correlation with mRNAseq data for each gene without probeset id which is used for correlation between clinical and methylation.