This is a test version of Biostars. For the public version, visit https://www.biostars.org.
Why there are no reads for gene quantification but many reads can be quantified for exon using featureCounts

Hi, I used featureCounts to quantitate whole genebody and exon-only region of the same gene using the same bam files, and unexpectedly found that exon-only region successfully assigned 4000k fragments while 0 fragments assigned whole genebody region, so I wonder why did this happen and how to quantify gene body region correctly?

featureCounts -T 10 -p -C -B -s 2 -a Mus_musculus.GRCm38.99.gtf -o exon.quant 19R774.sort.bam featureCounts -T 10 -p -C -B -s 2 -t gene -a Mus_musculus.GRCm38.99.gtf -o gene.quant 19R774.sort.bam

rna-seq exon quantification

1 answer

can you provide a bit more data/result to back up what you are saying? Is it for all genes/exons in the gtf file or only for part of them?

give some examples for instance for genes in which both approaches differ.

only part of them, and the gene for example:

grep ENSMUSG00000058207 gene.quant

ENSMUSG00000058207 chr12 104338486 104346144 + 7659 0

grep ENSMUSG00000058207 exon.quant

ENSMUSG00000058207 12;12;12;12;12 104338486;104340494;104342939;104344127;104345233 104338545;104341150;104343212;104344280;104346144 +;+;+;+;+ 2057 433393

hmm, that does not look quite correct.

just as with the gene approach you should get one line per exon. Do double check the formatting of the output (input?)

I'm sorry I didn't describe it clearly. Genequant=exon+intron region , exonquant means all exon region of the gene, so the result of exon.quant also one line per gene including all the exon region. Actually, I want to get reads abundance of intron region using genequant-exonquant.

using IGV to check ENSMUSG00000058207 reads abundance find high abundance in exon region which means the result of exon.quant is right while something wrong in gene.quant.

not sure I follow, but you can't get counts over two features? you can get counts for introns, for exons, for genes, but not for exon + intron features. These tools work on a feature mentioned in the third '?) column of you gff/gtf file

I use -t gene to count reads covering the full length of the gene which both include intron and exon region. so exon+intron =gene, one feature ,I don't know if my understanding is correct?

yes, that is correct. (I was temporarily under the impression you wanted to count on exon + intron feature, rather than gene as a feature)

I do notice that in the gene.quant you mention above it says 'chr12' and in the exon one is says '12' . can you verify this (and also make sure you are consistent in this for all files you use, thus all 12 or all chr12 )

Log in to answer this question.