[dpryan]

I would normally consider that extremely low. I normally get 50-80%, depending on the dataset (80% is more normal these days). Since you seem to be doing targeted resequencing, I wonder if the targeting isn't that great.

Are these alignments to the same reference that you sent me previously? If so, I can send you my email address and you can just email the compressed fastq files to me. I can then see if that's actually correct or if something is going wrong.

[GenoMax]

Would you by any chance know if 0.21% of reads being aligned is normal?

Answer may be no since it appears that your data can use some trimming.

n = 3 is not huge but since Devon went from 66% to 100% alignment hopefully that observation will work well for the remaining 25584 reads.

[dpryan]

Answer may be no since it appears that your data can use some trimming.

n = 3 is not huge but since Devon went from 66% to 100% alignment hopefully that observation will work well for the remaining 25584 reads.

I like to be optimistic

[mvijayen]

I thought so and am working with trim_galore right now. @dpryan: please do send me your e-mail address and I will e-mail the compressed fastq files to you. And yes, they are to the same reference.

[dpryan]

Just to update the forum, should someone get here via google later, the cause of the low alignment rate was not specifying "--local" in the command (otherwise, the alignment rate is ~85% for this dataset).

Part of the confusion arose from the fact that --local isn't a bison/bison_herd option, but rather is simply given to bowtie2. In hindsight, I never really explained anywhere how that works, so this sort of confusion was inevitable!

For the next release, I'll try to put together a little tutorial with different uses cases, of which some will use "pass-through" options like --very-sensitive-local so that it's more obvious how this works. Hopefully that will make everyone's life easier in the future