covid-truth-eval

Evaluate accuracy of covid assemblies where truth is available

Installation

Minimal instructions are below. Please see the wiki page for more details.

Get a Docker image of the latest release:

docker pull ghcr.io/iqbal-lab-org/cte:latest

All Docker images are listed in the packages page.

Alternatively, build your own Docker image:

sudo docker build --network=host .

Releases include a Singularity image to download. Each release has a file called cte_vX.Y.Z.img, where X.Y.Z is the release version.

Alternatively, build your own Singularity image:

singularity build cte.simg Singularity.def

Dependencies:

Install by cloning this repository (or downloading the latest release), and running:

python3 -m pip install .

To evaluate one SARS-CoV-2 consensus sequence, you will need:

A VCF file of the "truth" calls truth.vcf
The consensus sequence to evalaute in a FASTA file cons.fa
The primer scheme. Currently supported: COVID-ARTIC-V3, COVID-ARTIC-V4, COVID-MIDNIGHT-1200. Or use your own TSV file of primers in Viridian Workflow format.

The program is called cte and is installed in the Docker and Singularity containers, and gets installed by pip.

Example, assuming primer scheme COVID-ARTIC-V4:

cte eval_one_run \
  --outdir OUT \
  --truth_vcf truth.vcf \
  --fasta_to_eval cons.fa \
  --primers COVID-ARTIC-V4

The output files are:

results.tsv - a TSV file of counts of the truth bases vs what was called in the consensus. The same information is also put in a JSON file results.json.
per_position.tsv - a TSV file, one line per reference position. It shows the multiple alignment of the reference, truth (inferred from the truth VCF file), and the sequence being evaluated. At each position the assigned category of truth and called bases is shown, where the categories are the same as those used in results.tsv.

The files are described in detail in the output files documentation.