Hi all,
I’m currently using Tophat and bowtie2 to map 100bp PE RNA-Seq reads from a mixed human/bacterial sample. We’re more interested in the bacterial side of things, but there's plenty that we can learn from the human reads too. We originally used bowtie2 to map human reads to hg19, and then another bowtie2 to map bacterial reads. However we then switched to tophat for obvious reasons and redid the processing, and obviously a much larger number of human reads were mapping. But when we repeated the bowtie2 run for bacterial reads we had significantly less reads map.
We’ve also repeated tophat on a few different settings to try find whats optimal. The no-discordant option in tophat changes the results quite a lot both for the amount of human reads mapped, and the number of bacterial reads mapped. I haven’t looked into the biological outcomes of this yet, but the differences in the amount of reads has me concerned, and the bacterial reads that come out from the file that were preprocessed with tophat on the default settings the no-discordant run
I’ve looked into the differences between bacterial reads mapped by bowtie2 after tophat run with default settings and tophat run with the no-discordant option and they only share about 0.0007% of the bacterial reads, which is very odd.
Basically I’m wondering if anyone could shed light on why the different tophat parametres have such a huge impact on the amount of reads which bowtie2 later identifies as being bacterial??
Also any general advice would be appreciated
Thanks
I’m currently using Tophat and bowtie2 to map 100bp PE RNA-Seq reads from a mixed human/bacterial sample. We’re more interested in the bacterial side of things, but there's plenty that we can learn from the human reads too. We originally used bowtie2 to map human reads to hg19, and then another bowtie2 to map bacterial reads. However we then switched to tophat for obvious reasons and redid the processing, and obviously a much larger number of human reads were mapping. But when we repeated the bowtie2 run for bacterial reads we had significantly less reads map.
We’ve also repeated tophat on a few different settings to try find whats optimal. The no-discordant option in tophat changes the results quite a lot both for the amount of human reads mapped, and the number of bacterial reads mapped. I haven’t looked into the biological outcomes of this yet, but the differences in the amount of reads has me concerned, and the bacterial reads that come out from the file that were preprocessed with tophat on the default settings the no-discordant run
I’ve looked into the differences between bacterial reads mapped by bowtie2 after tophat run with default settings and tophat run with the no-discordant option and they only share about 0.0007% of the bacterial reads, which is very odd.
Basically I’m wondering if anyone could shed light on why the different tophat parametres have such a huge impact on the amount of reads which bowtie2 later identifies as being bacterial??
Also any general advice would be appreciated
Thanks
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