How to normalize-transform rsem.genes.results of TCGA RNA-seq v2?
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Last seen 5.2 years ago

Dear Bioconductor users,

I am working with TCGA RNA-seq data. I have downloaded the rsem.genes.result file for a specific cancer type  and I've understood that the "raw_count" is the estimated number of fragments derived from a given gene and the "scaled_estimate" is the fraction of transcripts made up by a given gene. The "scaled_estimate" could maybe be used as well, e.g. by multiplying it with 1M to get "transcripts per million" (TPM) which Li and Dewey state should be more comparable across samples. How exactly the "scaled_estimate" counts have been computed? Have these counts been scaled for library size or both library size and transcript length? Why the "scaled_estimate" column never sums to one? Could these counts be used for differential expression analysis applying Deseq2, limma-voom, edgeR algorithms?Could these values be normalized-transformed for further analyses (unsupervised learning, supevised learning) applying limma-voom or VST tranformed counts?

Thank you very very much for your time in advance!!!


Panagiotis Mokos

tcga rnaseq rsem R normalization • 2.0k views

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