I need to use featureCounts on the public available data from encode project for mm9 from Bing Ren lab. As far as I understood, the rna-seq is strand specific but I need to know the library type (ff-firststrand, ff-secondstrand, ff-unstranded, fr-firststrand, fr-secondstrand, fr-unstranded) to specify correctly the -s parameter of the featureCounts:
-s <int> Indicate if strand-specific read counting should be performed.
It has three possible values: 0 (unstranded), 1 (stranded) and
2 (reversely stranded). 0 by default.
There are a lot of posts related to this issue. I'd recommend you to give a try to infer_experiment.py script, inside RSeQC package. Read the manual, and if you get in troubles, you can always come back here.
I found out that I have single-end reads with the following configuration.
Does it mean that I need to use -s 2 for featureCounts and for cuffdiff fr-secondstrand?
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I had the same question in mind. I use the Kapa RNA-seq kit which is based on the dUTP method. We did this on bacteria RNA. As I understand from this post that we should use the -s 2 option. Honestly, I lack good understanding of why exactly we should use these options. I wished that the documentation were more specific.
These are the stats from different -s options:
-s 0 option:
Total fragments : 106454
Successfully assigned fragments : 87545 (82.2%)
-s 1 option:
Total fragments : 106454
Successfully assigned fragments : 15582 (14.6%)
-s 2 option:
Total fragments : 106454
Successfully assigned fragments : 72078 (67.7%)
So -s 0 is the highest because it combines all possible alignments and roughly equals the sum of -s 1 and -s 2.
This is the command line used:
featureCounts -g gene_id -t exon -f -O -T 1 -p -d 100 -D 1000 -s 2 -P -R -a file.gtf -o fileout file.bam
Please let me know if you think there is something wrong with these options. Many thanks
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microbe77 •
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