Sequence length statistics

[Nicholas_Bokulich]

@Joanna

The percentile (see the picture at the top of this discussion or below this comment) indicates a bigger range than expected. I wonder what would you do in this situation? Would you leave as it is or it is better to filter them out based on the expected length?

That variation is much more than usual, indeed. There is another related discussion somewhere on the forum (I can't find it right now) where it was mentioned that this variation is usually related to non-target DNA... e.g., chloroplast + mitochondrial 16S is shorter than bacterial, and sometimes some eukaryote 18S can be hit by the primers. So unless if this is something that interests you, you should just filter out anything too long/short. I'd say filter anything < 240 nt or > 255 nt

@MirjamBloem

1. It may also be that very short/long reads will not be classified and filtered out after taxonomy? This would make it not necessary to filter the reads after denoising based on the read length statistics.

You are correct @MirjamBloem it depends on what this is, but if it is non-target DNA (e.g., eukaryote) it will probably not classify so just removing it now will save you time.

@MirjamBloem

• how it can be that when (mistakely) eliminating the last 20 bp using the ‘trun’ setting i have more consistent read lengths compared to not cutting the last 20 bp and

Not sure! Could be that truncating the last 20 nt is causing the unusually long seqs to filter out at that stage (since they no longer join) but I can't explain the shorter seqs.