Closed sagrudd closed 4 years ago
Thanks for this, I'll take a look in a bit.
Dear @sagrudd I merged this in haste:
Did you mean: if get_read_mean_quality(rec) < args.quality: ??
Also what is purpose of: r = random() if r >= args.sample: continue
(1) - get_read_mean_quality(rec) < args.quality - is a filter for mean read quality (as calculated by Biopython) - this is working towards reduction of the total number of reads in cases where read-count is high (I know that the minion step can also subsample) - I intended '<=' here since if I ask for a read filter at Q=7.5 I would like reads with Q of 7.5 included - the actual impact of using '<' will be negligible
(2) - I have included a parameter for sub-sampling large sequence collections (args.sample) - again for reasons of reduction if there is a silly excess of reads. random()
returns a float scaled between 0..1 - sample should be a float - if I specify a subsample of 0.25 - we will skip any reads where the random value is >= 0.25 and thus should reduce the data dimension accordingly
This value is 1 by default and no-skipping will be performed
Pleased to chat offline if this would be more productive?
1) yeah but the logic was inverted in the original code, i.e. it was dropping anything with Q>7
2) gotcha!
d'oh! would you like me to submit a merge request for (1) or can you change? Apologies for the muppetness here ...
Dear Nick, PR here is aiming to provide some basic support for running the ARTIC workflow on sequence data that has already been demultiplexed by Guppy - following feedback from users in China there is a case for removing the requirement for the sequencing summary file for medaka workflow. To make this workflow minimally instrusive to existing code I have created a target called
guppyplex
in the pipeline.py - this aims to provide equivalent functionality to both thegather
anddemultiplex
steps. I also have a snakefile for the automation of the workflow - would you like that committed here too - would welcome your thoughts here - very pleased to discuss further offline - Cheers - S