I am interested in performing differential gene expression analysis of RNASeq data in two conditions with a number of biological replicates for each condition. I have obtained gene-level FPKMs for each sample. As gene-level FPKMs should be properly normalized, comparing the expression of a single gene using FPKM across multiple samples should be reasonable. Thus, my simple strategy is this:
use a two-sample, unpaired Mann-Whitney (Wilcox) test on the FPKMs for each gene in the two groups and correct for multiple hypothesis testing.
I have a few questions regarding this approach. First, is it valid? Second, would this approach be valid for other RNASeq normalization methods (in particular Transcripts per Million (TPM) generated by RSEM)? Third, how is this approach better or worse than either count-based methods (e.g. DEGSeq/edgeR) or other commonly used methods (e.g. Cuffdiff)?
use a two-sample, unpaired Mann-Whitney (Wilcox) test on the FPKMs for each gene in the two groups and correct for multiple hypothesis testing.
I have a few questions regarding this approach. First, is it valid? Second, would this approach be valid for other RNASeq normalization methods (in particular Transcripts per Million (TPM) generated by RSEM)? Third, how is this approach better or worse than either count-based methods (e.g. DEGSeq/edgeR) or other commonly used methods (e.g. Cuffdiff)?
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