SARS_COVinfections

A co-infection detection pipeline focusing on SNP call frequencies.

In each sample, the pipeline consider genomic positions where the alternative allele frequency is ≥85% (homozygous SNPs); positions where more than one allele coexists and the major allele frequency is between 15 and 85% (heterozygous SNPs); and positions where the alternative allele is ≤15% and is considered background sequencing noise and therefore excluded.

1. Install and activate conda environment

git clone https://github.com/MG-IiSGM/SARS_COVinfections
cd SARS_COVinfections
conda env update -n sars_covinf --file SARS_COVinfections.yml
conda activate sars_covinf

2. Run the python pipeline

python Cov-infection.py -i test_fastq \
  -r reference/COVID_ref.fasta -o test \
  -t 4 -p primers/nCoV-2019.bed

Mandatory arguments:

-i: input directory of paired fastq files.
-r: reference genome in fasta format.
-o: output directory. If it does not exist, it will be created.
-t: Number of threads.
-p: Primers used for sequencing.

Optional arguments:

--min_DP: minimum frequency (depth) to accept a SNP.
--min_HOM: minimum proportion for homocygosis.
--ambiguity: minimum confident fraction to segregate.
--pangolin: pangolin annotation.
--snipit: snipit visualisation of SNPs.

To see all available options:

python Cov-infection.py -h

Output generated

The output directories created are

• Bam: Bam file with reads mapped to reference.

• Consensus:

  • ivar consensus fasta
  • Co-infection output folder:
    • ALN: Visual representation of HTZ positions.
    • Sequences: Majority (2) and Minority (1) sequences.
    • Stats: Co-infection statistics.

• Quality: Fastq quality.

• Stats: Coverage and bam stats.

• Trimmed: Fastq trimmed.

• Variants: tsv file with SNVs.

If you use SARS_COVinfections pipeline, please cite our publication:

Peñas-Utrilla, D., Pérez-Lago, L., Molero-Salinas, A. et al. Systematic genomic analysis of SARS-CoV-2 co-infections throughout the pandemic and segregation of the strains involved. Genome Med 15, 57 (2023). https://doi.org/10.1186/s13073-023-01198-z