VEP to annotate variants, and I believe selects the default Ensembl transcript to use for annotation. Sometimes the transcript that
VEP selects is not the transcript I'm interested in, usually because the selected transcript is not the most highly expressed transcript in my tissue of interest (skin).
vcf2maf allows you to provide a transcript override list so that VEP annotates the variant using the specified transcripts instead.
I have several skin samples sequenced with bulk RNA-Seq. I want to estimate the average abundance for each transcript across all samples and then use these abundances to rank transcripts from most to least abundant. Then I will use the most abundant transcript as the default VEP transcript. I plan to use
kallisto to quantify transcript abundance. Should I use TPM or normalized counts to calculate average expression?
My initial thought is to use normalized counts (generated by DESeq2 from raw counts). Are there any problems with this approach? GTEx displays transcript abundance with average TPM, but I thought TPM was inappropriate to use across samples because it doesn't account for between sample differences.
Update: I forgot to mention I also tried using TPM ranks like @ATpoint describes. I haven't fully compared how this compares to transcripts identified by normalized counts, but the initial genes I checked showed good concordance between methods