A simple pipeline for the assembly, consensus calling and annotation of COVID.
This pipeline is somewhat dependent on folder structures and naming schemes used by the HPC/sequencing core at Icahn School of Medicine.
It also has the primer set hard-coded.
Please ensure you understand how it works and what changes will need to be made if you plan on running on your own data. I am happy to help (time permitting) so please reach out.
cd <this directory>
conda env create --file env.yml
conda activate COVID
you may need to update conda before creation
conda update conda
python run_pipeline.py -p <pacbio_ccs_reads.fastq> -o <path/to/output>
Threads can be specified with -t
python run_pipeline.py -i <sample_folder>
The following folder structure should exist
└───<reads_15kb_primers>'
│ │ <read_prefix>_1.fastq.gz
│ │ <read_prefix>_2.fastq.gz
│
└───<reads_2kb_primers>
│ <read_prefix>_1.fastq.gz
│ <read_prefix>_2.fastq.gz
n.b. can be run on one to as many read files as needed, each pair of reads should have it's own folder.
will create pipeline folder in <sample_folder> with output.
Finally to run QC do python run_QC.py -i <sample_folder> -kb /path/to/kraken_db
on any <sample_folder> that has run successfully.