Question: read counts of paired end reads for DESeq2 analysis
0
gravatar for tszn1984
3.6 years ago by
tszn19840
tszn19840 wrote:

I got a  list of paired end bam files, and want to do DESeq2 analysis. The first thing is to count the reads at gene level. I tried feature counts. However, it requires reorder of the bam files if I specified paired end is True, which takes infinite time for my huge dataset. I also tried summarizeOverlaps, which also takes very long time. 

Is there any tools could quickly count the paired end reads for DESeq2 at gene level? Thanks.

deseq featurecounts paired • 763 views
ADD COMMENTlink modified 3.6 years ago by Steve Lianoglou12k • written 3.6 years ago by tszn19840
2

Are you using the latest version of featureCounts (part of Rsubread package)? Running time for re-ordering read pairs has been significantly reduced in recent releases of featureCounts. FeatureCounts now only needs to re-order a small portion of read pairs instead of re-ordering all read pairs as it performed in older version. It now takes featureCounts less than one minute to count 30 million read pairs with 4 threads (this includes the read re-ordering time).

ADD REPLYlink written 3.6 years ago by Wei Shi3.2k
Answer: read counts of paired end reads for DESeq2 analysis
1
gravatar for Steve Lianoglou
3.6 years ago by
Denali
Steve Lianoglou12k wrote:

If you're looking for speed, you might try using kallisto or salmon to quantitate expression from your data, then use the tximport package to roll the transcript-level estimates up into gene level estimates so you can feed those numbers into DESeq2 (or edgeR (or voom)).

Note that, technically, you will have to be running the development version of Bioconductor to get tximport ...

ADD COMMENTlink written 3.6 years ago by Steve Lianoglou12k

Yes, I'd try that, and add that tximport will be in the release branch in about a week (~May 4).

Also, for featureCounts, you could name-sort your BAM files using samtools with multiple threads...

ADD REPLYlink written 3.6 years ago by Michael Love26k
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