I know this is probably a very old (and sadly still ongoing) topic, but I would like your advice anyway.
I have RNAseq data processed in TETranscript for 7 different Zebrafish tissues (testis, ovary, heart, kidney ...). I am not strictly interested in DE analyses (at least not yet), as I just want to normalize the counts and make a heat map to compare expression across tissues. Given that there is not even a real treatment (might be the testis, but it's not even easy to justify it), I was wondering how should I set up the normalization, and which program or method to use.
TETranscript by default provides a DeSeq R script for data analysis, and I've seen the section in the manual relative to "DESeq without replicates", so I was thinking of modifying the default TETranscript script and simply go for that.
I am not an expert in the math and statistics behind the normalization process, so I can't judge what is the more reasonable approach, if using DESeq, DESeq2 (and how, maybe using FKPM or TPM?) or EdgeR (e.g., d = calcNormFactors(d) ; n = cpm(d, normalized.lib.sizes = TRUE)).
Thank you so much for your help,