Pychopper is used to identify, orient and trim full-length Nanopore cDNA reads. The tool is also able to rescue fused reads.

• pychopper on GitHub

• Module Name: pychopper (see the modules page for more information)
• pychopper can use multiple CPUs. Please match your allocation with the number of threads used. pychopper does not scale efficiently to more than 8 CPUs
• pychopper ≤ 2.4.0 cannot natively read gzip input. ≥2.7.1 can read gzip files but it is inefficient. It remains more efficient to uncompress input to lscratch for processing.
• pychopper often reads the fastq file twice. Therefore it's best to move/unpack fastq files into lscratch. See example below.
• -m edlib is associated with stalled runs and should probably be avoided.
• Example files in $PYCHOPPER_TEST_DATA
• the command cdna_classifier.py was renamed to pychopper between 2.4.0 and 2.7.1

Allocate an interactive session and run the program. Sample session:

[user@biowulf]$ sinteractive --mem=10g --cpus-per-task=6 --gres=lscratch:10
salloc.exe: Pending job allocation 46116226
salloc.exe: job 46116226 queued and waiting for resources
salloc.exe: job 46116226 has been allocated resources
salloc.exe: Granted job allocation 46116226
salloc.exe: Waiting for resource configuration
salloc.exe: Nodes cn3144 are ready for job

[user@cn3144]$ cd /lscratch/$SLURM_JOB_ID
[user@cn3144]$ module load pychopper/2.7.10
[user@cn3144]$ cp $PYCHOPPER_TEST_DATA/SIRV_E0_pcs109_25k.fq.gz .
[user@cn3144]$ pychopper -r report.pdf -u unclassified.fastq -t $SLURM_CPUS_PER_TASK \
                    -w rescued.fastq SIRV_E0_pcs109_25k.fq.gz - | gzip -c > /data/$USER/temp/full_length.fastq.gz
Using kit: /opt/conda/lib/python3.12/site-packages/pychopper/primer_data/cDNA_SSP_VNP.fas
Configurations to consider: "+:SSP,-VNP|-:VNP,-SSP"
Total fastq records in input file: 25000
Tuning the cutoff parameter (q) on 9465 sampled reads (40.0%) passing quality filters (Q ≥ 7.0).
Optimizing over 30 cutoff values.
100%|████████████████████████████████████████████████████████| 30/30
Best cutoff (q) value is 0.3448 with 88% of the reads classified.
Processing the whole dataset using a batch size of 4166:
 94%|██████████████████████████████████████████████████      | 23614/25000
Finished processing file: input.fastq
Input reads failing mean quality filter (Q < 7.0): 1386 (5.54%)
Output fragments failing length filter (length < 50): 0
-----------------------------------
Reads with two primers: 86.93%
Rescued reads:          3.16%
Unusable reads:         9.91%
-----------------------------------

Move the rescuted and unclassified reads and the reports if you need them before ending the session.

[user@cn3144]$ gzip -c rescued.fastq > /data/$USER/temp/rescued.fastq.gz
[user@cn3144]$ gzip -c unclassified.fastq > /data/$USER/temp/unclassified.fastq.gz
[user@cn3144]$ mv report.pdf /data/$USER/temp
[user@cn3144]$ exit
salloc.exe: Relinquishing job allocation 46116226
[user@biowulf]$

Create a batch input file (e.g. pychopper.sh), which uses the input file 'pychopper.in'. For example:

#!/bin/bash
module load pychopper/2.7.10 || exit 1
cd /lscratch/$SLURM_JOB_ID
cp $PYCHOPPER_TEST_DATA/SIRV_E0_pcs109_25k.fq.gz .
pychopper -r report.pdf -u unclassified.fastq -t $SLURM_CPUS_PER_TASK \
    -w rescued.fastq SIRV_E0_pcs109_25k.fq.gz - | gzip -c > /data/$USER/temp/full_length.fastq.gz
gzip -c rescued.fastq > /data/$USER/temp/rescued.fastq.gz
gzip -c unclassified.fastq > /data/$USER/temp/unclassified.fastq.gz
mv report.pdf /data/$USER/temp

Submit this job using the Slurm sbatch command.

sbatch --cpus-per-task=6 --mem=10g pychopper.sh

Create a swarmfile (e.g. pychopper.swarm). For example:

pychopper -t $SLURM_CPUS_PER_TASK input1.fastq.gz - \
  | gzip -c > /data/$USER/temp/full_length1.fastq.gz
pychopper -t $SLURM_CPUS_PER_TASK input2.fastq.gz - \
  | gzip -c > /data/$USER/temp/full_length2.fastq.gz

Submit this job using the swarm command.

swarm -f pychopper.swarm -g 10 -t 6 --module pychopper/2.7.10