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RNAseq Normalization for eQTL Mapping?

How do you normalize RNAseq data for eQTL mapping?

I have 200 samples with bulk RNAseq data, from that I generated matrix of TPM values for each gene. I also have a matrix of expected alignment counts and a matrix of read counts.

I suppose I should use TPM for the eQTL mapping. If so, how do I normalize the values? Do I perform a quantile normalization or some other method? Should I even normalize the TPM matrix?

Additionally, what TPM cutoff should I apply and should I exclude genes according to X% of samples with TPM expression over Y_TPM_CUTOFF?

Thanks!

eqtl rna-seq qtl genetic mapping

It will likely depend on the eQTL program that you're using and the type of data distribution that it expects. Which one are you aiming to use?

Hi Kevin! [Sorry for jumping in on this question... :P ] I would like to perform an eQTL mapping analysis using QTLtools or fastQTL, but I am not sure how I should normalize or transform the count/expression data. [I noticed that if I use just regular DESeq2-normalized values, or variance stabilized transformed values, the results are pretty similar. But which one is best to use (and why)?]

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