Counting exonic reads with DEXSeq and GenomicAlignments
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igor ▴ 40
@igor
Last seen 3 months ago
United States

The DEXSeq vignette describes several protocols for obtaining exon counts. One option is to use the dexseq_count.py script (powered by htseq) that comes with the package. Another option is to use summarizeOverlaps directly in R. I tried both methods with unstranded parameters and the results were identical (based on a few genes). However, stranded settings yield very different results. Some exons are off by a few reads, but some can be as low as half. I used the settings as specified in the vignette, which I assumed would be most appropriate. I also tried adjusting parameters, but it didn't help.

The command for dexseq_count.py:

python /path/DEXSeq/python_scripts/dexseq_count.py \
--format bam \
--order pos \
--paired yes \
--stranded reverse \
$ref_gff \$bam \
\$counts_txt

The command for GenomicAlignments:

txdb = makeTxDbFromGFF(file = genes_gtf, format = "gtf")
exons = disjointExons(txdb, aggregateGenes = FALSE)
SE = summarizeOverlaps(features = exons, reads = bam_list, singleEnd = FALSE,
ignore.strand = FALSE, inter.feature = FALSE, fragments = TRUE)

Is there a mistake with one of the methods?

dexseq genomicalignments exon usage • 716 views