Read counts at gene and transcript level - hisat2+Featurecounts or Stringtie?+deseq2
0
1
Entering edit mode
12 months ago
tianshenbio ▴ 110

I hope to do DE analysis at both gene and transcript level.

First I mapped the reads to the genome using hisat2. Now I need to generate a raw count matrix for deseq2.

Since I have a well-annotated gff file, I am not interested in finding new isoforms. If I chose Stringtie, it would only be used to generate raw count matrix. And it can calculate both gene and transcript in one run (right?). If I chose Featurecounts, I have to run it twice, for gene and transcripts separately. But someone told me Featurecounts is not suitable to quantify isoforms...

What would be a better choice?

RNA-Seq featurecounts stringtie hisat2 deseq2 • 779 views
ADD COMMENT
0
Entering edit mode

for instance salmon is well suited for isoform quantification (better than FeatureCounts of HTseq-count indeed)

with 'gene' you mean gene-locus and "transcript' = isoform(s), correct?

ADD REPLY
0
Entering edit mode

Yes, with 'gene' I will count reads mapped to all exons of that gene locus, with 'transcripts' I hope to quantify isoforms. Is Stringtie suitable for isoform quantification as well?

ADD REPLY
0
Entering edit mode

not sure if I (can) agree with your approach here :/

sorry, don't have much hands-on experience with StringTie, but I know it can (and is used) for creating de-novo transcripts (and isoforms) from mapped reads. Others will chip in here I assume.

ADD REPLY

Login before adding your answer.

Traffic: 1267 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6