Lexogen QuantSeq quatification - Salmon vs Star/Bowtie followed by htseq

[tamuanand]

Hi

I have posted this question on GitHub - https://github.com/COMBINE-lab/salmon/issues/365 and I hate to cross-post. I am not sure if this google groups forum is the better home for my question or GitHub..Given this, I am just going to copy/paste what I asked on GitHub - my apologies..

I have a general question pertaining to quantifying QuantSeq data and comparing Salmon vs the alignment methods recommended by Lexogen (Star/Bowtie followed by htseq to get read counts per gene). Has anyone compared the 2 methods - would be very interested to know the findings.  I happen to see this issue which is still stated as "Open" - probably it should be marked as Closed?

Based on the above issue and also this issue, I assume using --noLengthCorrection would be the recommended way to use Salmon for quantifying QuantSeq data - is that right?

In general, I am planning to use Salmon this way:

1. index the transcriptome
2. salmon quant -i {input.index} -l A -1 {input.R1} -2 {input.R2} -o {output} --noLengthCorrection --validateMappings --gcBias --seqBias --posBias

While using Salmon for quantification, are there any subtleties to be aware of based on the QuantSeq protocol (FWD vs REV) ?

Please advise.

Thanks in advance,