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I have been comparing HTSeq (htseq-count) counts to TPMcalcualtor UniqueReads counts.
I find them generally to be in very good agreement. However, there are occasionally some cases where HTSeq and TPMcalculator will be in agreement for the "Reads" column of TPMcalculator output. but will disagree in the last 8 columns (TPMcalculator output will report zeros).
This can happen with genes that receive just a few reads or with genes have 10's of thousands of reads aligning. It can happen with intronless genes or with multi-exon genes.
Since I'm using de novo assembly and annotation, I'm wondering if there could be something about my gff file that is tripping up TPMcalculator?
These discrepancies appear to be instances of overlapping genes in the gff (opposite strands) where TPMcalculator can't assign one transcript as the correct strand so there are no unique reads assigned to EITHER transcript.
Not sure if there's a way to fix this within the TPMcalculator? (I don't seen an option to enforce stranded-ness)
I have been comparing HTSeq (htseq-count) counts to TPMcalcualtor UniqueReads counts.
I find them generally to be in very good agreement. However, there are occasionally some cases where HTSeq and TPMcalculator will be in agreement for the "Reads" column of TPMcalculator output. but will disagree in the last 8 columns (TPMcalculator output will report zeros).
For example:
DTO2_FUN_009269 scaffold_6 3072673 3073284 612 366201 9037.3 612 366201 7579.98 0 0 0 0 0 0 0 0 0 0 0 0
This can happen with genes that receive just a few reads or with genes have 10's of thousands of reads aligning. It can happen with intronless genes or with multi-exon genes.
Since I'm using de novo assembly and annotation, I'm wondering if there could be something about my gff file that is tripping up TPMcalculator?
Here's my gff file for the example case above
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