Introduction

This is a pipeline for drug-resistance profiling from HIV whole genome NGS data. It takes in a HIV reference genome (currently HXB2) and a dataset of reads in (gzipped) fastq format, and performs the following steps:

1. aligns the reads to the reference,
2. performs variant calling, and
3. queries the HIVDB system for the presence and degree of drug resistance (requires internet connection).

Currently, the pipeline uses Bowtie2 for Step1, Lofreq for Step 2, and sierrapy for Step 3.

This code is under development. We hope to test and add more options.

Installation

This pipeline requires the package manager Conda and the workflow management system Snakemake. All other dependencies are handled automatically by Snakemake.

Install Conda

Download Miniconda3 installer for Linux from here, or for macOS from here Installation instructions are here. Once installation is complete, you can test your Miniconda installation by running:

$ conda list

Install Snakemake

Snakemake recommends installation via Conda:

$ conda install -c conda-forge mamba
$ mamba create -c conda-forge -c bioconda -n snakemake snakemake

This creates an isolated enviroment containing the latest Snakemake. To activate it:

$ conda activate snakemake

To test snakemake installation

$ snakemake --help

Download the pipeline

Clone this pipeline by clicking the Clone button on the top-right of this page, or download it by clicking the ellipsis next to the Clone button.

Quickstart Guide

Let's try running the pipeline on sample data provided in the test_data folder. With the snakemake conda environment activated, and from the top-level directory (i.e. the one that contains this readme file), run:

snakemake --use-conda --configfile config/config.sample.yaml -np

to do a dry-run. If snakemake does not complain and everything seems ok, then run:

snakemake --use-conda --configfile config/config.sample.yaml --cores all

The results can be found inside the newly created directory called test_result. Interpretation of drug-resistance as provided by sierrapy can be found inside the drug_resistance_report folder. Intermediate files such as the read-to-reference alignments and variant calls can be found in their respective folders.

Running the pipeline on your own data

To the run the pipeline on your own data, you need to specify in a config file (in YAML format) the paths to the input data (reads and reference), path to the output directory. Optionally, in this config file, you can also set parameters for the various tools that make up this pipeline. You can use config/config.template.yaml as a template. Once the configfile is ready, run the pipeline like above:

snakemake --use-conda --configfile /path/to/configfile -np

for a dry run, and

snakemake --use-conda --configfile /path/to/configfile --cores all

for the actual run.

Contact

This is an ongoing work. If you have questions, concerns, issues, or suggestions, please contact: Anish Shrestha, Bioinformatics Lab, De La Salle University Manila at [email protected] .