ncov-qa is the workflow used for the quality assessment of COVID-19
data from participating institutes in Ontario. Each institute provides
results from FAST5/FASTQ files distributed by Public Health Ontario.
Download the ncov-qa package from GitHub.
git clone https://github.com/simpsonlab/ncov-qa
cd ncov-qa
It is highly recommended to use conda to install dependencies and
tools:
conda env create -f workflow/envs/environment.yaml
Once the dependencies have been installed, activate the conda environment:
conda activate ncov-qa
The files submitted by each institute include:
-
summary_qc.tsv -
consensus.fasta -
lineage_report.csv
These files should reside or be linked in a data directory.
A config.yaml file is required to run the pipeline. The file should use the following as a template:
institute_id: "<institute_prefix>"
submitter: "Submitter"
data_root: "data"
consensus_pattern: "{data_root}/{sample}.fasta"
reference: "/path/to/reference_genome.fasta"
mode: "vcf"
summary_sample_name: "{sample}"
To run the pipeline:
snakemake -s /path/to/ncov-qa/workflow/Snakefile --cores num_cores build_snpeff_db
snakemake -s /path/to/ncov-qa/workflow/Snakefile --cores num_cores all
.
├── config.yaml
├── data
├── lineages
│ ├── <institute>_lineage_report.csv
│ └── <institute>_pangolin_version.txt
├── qa_align
├── qa_results
│ └── <institute>.mutation.metadata.tsv
├── snpEff_genes.txt
└── snpEff_summary.html
To create a merged count table:
python /path/to/ncov-qa/scripts/merge_qa_results.py --file /path/to/output/qa_results/<institute>.mutation.metadata.tsv --ref_file /path/to/baseline/output/qa_results/<institute>.mutation.metadata.tsv
- The
quick_align.pyscript was obtained from ncov-random-scripts
-
Richard J. de Borja richard.deborja@oicr.on.ca
-
Jared T. Simpson
MIT