I would like to use Deseq2 for normalization of RNA seq data, I need to compare the expression of a gene in different samples. Is there any way I can do normalization in DeSeq2 and download the data into CSV, then I can use excel to analyze the data ? Please tell me cpm matrix can be considered as normalized data, i know that CPM matrix is created based upon design matrix. In my case, I used primary tumor and normal sample. But, going forther I will need to compare between groups with in Primary tumor.Thanks so much in advance.
If you want to use DESeq2 to produce normalized counts you can do:
dds <- estimateSizeFactors(dds) mat <- counts(dds, normalized=TRUE)
If you want to produce CPMs with DESeq2 you can do:
mat <- fpm(dds)
Note that the fpm() function will produce CPMs which do not necessarily add up to 1e6, because it is using a robust definition of library size instead of the column sum.
What you do with these values downstream is up to you.