Hi,
This question is to the people who have worked with RRBS methylation data and RNASeq data. I have RRBS methylation data for cell lines and the RNASeq data for the same cell lines. For RNASeq data I have used cuffdiff program for differential expression analysis but I am not quiet happy with it as it does not give per sample fpkm or read count information so that I can compare the expression in groups with the expression of each sample in those groups to validate the results of differential expression analysis. I would like to use other method of differential expression but I have a question that since I will be integrating the data with RRBS, should I consider only the method which generates the read counts in fpkm units(like cufflinks-cuffdiff)? I am thinking this because fpkm normalizes the reads by transcript length which other methods do not.
My second question is that is there a standard method to integrate RRBS methylation data and RNASeq paired end data?
Any suggestions will be greatly appreciated. Thanks.
This question is to the people who have worked with RRBS methylation data and RNASeq data. I have RRBS methylation data for cell lines and the RNASeq data for the same cell lines. For RNASeq data I have used cuffdiff program for differential expression analysis but I am not quiet happy with it as it does not give per sample fpkm or read count information so that I can compare the expression in groups with the expression of each sample in those groups to validate the results of differential expression analysis. I would like to use other method of differential expression but I have a question that since I will be integrating the data with RRBS, should I consider only the method which generates the read counts in fpkm units(like cufflinks-cuffdiff)? I am thinking this because fpkm normalizes the reads by transcript length which other methods do not.
My second question is that is there a standard method to integrate RRBS methylation data and RNASeq paired end data?
Any suggestions will be greatly appreciated. Thanks.
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