Skip to content

kneubehl/nanopore

 
 

Repository files navigation

Scripts for processing short amplicon reads from Oxford Nanopore. For details, please see:

ST Calus, UZ Ijaz, and A Pinto. NanoAmpli-Seq: A workflow for amplicon sequencing from mixed microbial communities on the nanopore sequencing platform. bioRxiv 244517, 2018. DOI:10.1101/244517

Sam Young

dependencenies needed

psutil

biopython

concurrent

Modified the program to run in python3 then add in multprocessing to decrease time overall. Ran several test to see what preformed the best. Decreased the overall time by about half for the changing it to python3.

Speed test conclude that 3 cores are leads to the greatest is the amount of time effiecent. Multithreading is not optimal for chopping up sequences it lead to the slows amount of time. Just transitioning the older code into python3 reduced time significantly and then calling the imports directly decreased time.

linux terminal or mac terminals

First make sure your default python = python3

./chopSEQ.py -h this can help you understand some of the changes add into since last time

python3 chopSEQ.py -h

This will allow the computer to run on three cores hopefully will maximum the timing

./chopSEQ.py -i input_file -f foward_primer -r reservser_primer -p 3 > output_file

python3 chopSEQ.py -i input_file -f foward_primers -r reverse_primeRs -p 3 > \ >> output_file

this will allow the user to run on a single processor

./chopSEQ.py -i input_file -f foward_primer -r reverse_primer > output_file

python3 chopSEQ.py -i input_file -f foward_primer -r reversre_primer > \ >> output_file

i7-4970 CPU @ 3.60 Ghz on chopSEQ running times only using python3

Legend

best time 1

data sets No. total seqs proccesing used type times
sample_Travis2_p2.fa 419 Multithreading 1:49:06
sample_Travis2_p2.fa 419 Single core 1:19:54
sample_Travis2_p2.fa 419 Two cores
sample_Travis2_p2.fa 419 Three cores
sample_Travis2_p2.fa 419 Four cores
sample_Travis2_p2.fa 419 Five cores
sample_Travis2_p2.fa 419 Six cores
sample_Travis2_p2.fa 419 Seven cores
sample_Travis2_p2.fa 419 Eight cores 1:15:52
sample_Travis2_p4.1.fa 589 Multithreading 1:17:29
sample_Travis2_p4.1.fa 589 single core 58:05
sample_Travis2_p4.1.fa 589 two cores 35:18
sample_Travis2_p4.1.fa 589 three cores 31:43
sample_Travis2_p4.1.fa 589 four cores 36:31
sample_Travis2_p4.1.fa 589 five cores 40:23
sample_Travis2_p4.1.fa 589 six cores 43:27
sample_Travis2_p4.1.fa 589 seven cores 42:36
sample_Travis2_p4.1.fa 589 Eight cores 43:05
sample_Travis2_pcombined.fa 1008 Multithreading 3:11:07
sample_Travis2_pcombined.fa 1008 Single core 2:10:12
sample_Travis2_pcombined.fa 1008 Two cores 1:26:07
sample_Travis2_pcombined.fa 1008 Three cores 1:24:22
sample_Travis2_pcombined.fa 1008 Four cores 1:27:41
sample_Travis2_pcombined.fa 1008 Five cores 1:32:11
sample_Travis2_pcombined.fa 1008 Six cores 1:40:26
sample_Travis2_pcombined.fa 1008 Seven cores 1:50:24
sample_Travis2_pcombined.fa 1008 Eight cores 1:53:41

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%