Should I use the 'normalized_count' or the 'raw_count' as the input for edgeR or DESeq? They are in different files from one sample. One is in '._expression_rsem_gene_normalized.txt' and the other one is in '.rsem.gene.results'.
Hi all:
I'm working on TCGA's data. As we know, we can get '_expression_rsem_isoforms_normalized.txt', '_expression_rsem_isoforms.txt', '_expression_rsem_gene_normalized.txt', '_expression_rsem_gene.txt' of a sample from the RNASeqV2. I have these question:
- Which file should I use to calculate the DEG(differentially expressed gene)? I thought it's '_expression_rsem_gene_normalized.txt'. Is it right?
So if I wanna to get the DEG from the RNASeqV2 data, which tool/method should I use to get? Is t.test applicable for the analysis?
Thanks in advance!
1 answer
I haven't actually looked at these files, but it sounds like '_expression_rsem_gene_normalized.txt' is probably what you want. The authors mention in their RSEM paper that their output includes 2 values: (1) an estimate of the number of fragments that are derived from a given isoform or gene (similar to read counts) and (2) estimated fraction of transcripts made up by a given isoform or gene. They mention that the first value can be used as input to edgeR or DEseq to determine DE genes. If both of these values are available from TCGA, I would suggest using one of these methods over a simple t-test as they were designed with RNA-Seq data in mind.
I would use the raw counts - edgeR and DESeq have their own normalization steps.
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