STAPAMRTime 0.0.1

Metagenomic AMR variant detection tool, part of ARMTime.

Table of contents

• General info
• Setup
• Usage
• Output
• License

General info

This repo contains the necessary workflow for detecting antimicrobial resistance gene (AMR) variant in metagenomic data.

Input: Paired-end illumina reads (.fastq, .fastq.gz), reference CARD database and SNP data (card.json, snp.txt).

Output: detected AMR SNPs

Workflow:

1. Using card.json and snp.txt, a reference fasta file is created for each ARO that contain SNPs.
2. Reads are aligned to the reference fasta using bowtie2 in very-sensitive mode.
3. Generate alignment pileup with samtools, include all positions. This step can be fine-tuned by specifying MAPQ quality(i.e. --MAPQ)
4. For each variant in snp.txt, scans the pileup file for that ARO+position, record the detected base, and depth.
5. Calculate support values with base depth and count of variants detected.
6. Filter according to tuning parameters (i.e. --max-recall, --max-precision).
7. Output summary file(tab delimited).

Setup

Dependencies: biopython=1.72, numpy, pandas, bcftools, samtools, and bowtie2.

It is suggested to run this program within a conda environment. These dependencies can be installed from env.yaml using conda env create -f env.yaml

Following environment installing, clone this repo into any directory and see python main.py --help

At somepoint, this will be build into a conda package.

Usage

python main.py --forward /path/to/forward.fq --reverse /path/to/reverse.fq --card-json /path/to/card.json --card-snp path/to/snps.txt

At somepoint, the default behavior for --card-json and --card-snp will be to download the latest copy from card.mcmaster.ca unless specified. For now, you must specify it's path.

Example

See test/ for examples. To run the workflow using these test files:

python main.py --forward ./test/synthetic_1.fq --reverse ./test/synthetic_2.fq --temp ./example --card-json ./test/card.json --card-snp ./test/snps.txt --max-recall

This will generate an output folder called example and a result file called example_DetectedVariants.tsv

Output

The output is a tab delimitted file containing the following information:

Column	Description
ARO	ARO of resistance gene
VariantClass	CARD Model Type
VariantType	Mutation Type
ResistantVariant	Flag for Resistant Variant
SNP	Detected SNP
Depth	Total depth of the SNP position
AbsSupport	Number of reads matching the SNP
RelativeSuppor	%of resistant reads to total reads
INFO	Raw counts of alternate variants

Contribute

Any contributions are welcomed.

1. Fork it!
2. Create your feature branch: git checkout -b my-new-feature
3. Commit your changes: git commit -am 'Add some feature'
4. Push to the branch: git push origin my-new-feature
5. Submit a pull request :D

License

GNU General Public License v3.0

Permissions of this strong copyleft license are conditioned on making available complete sourcecode of licensed works and modifications, which include larger works using a licensed work, under the same license. Copyright and license notices must be preserved. Contributors provide an express grant of patent rights.