Skip to content
/ ARDaP Public

Comprehensive resistance detection from WGS data

Notifications You must be signed in to change notification settings

dsarov/ARDaP

Folders and files

NameName
Last commit message
Last commit date

Latest commit

author
Derek Sarovich
Oct 22, 2019
4c585cb · Oct 22, 2019
Sep 26, 2019
Jul 31, 2019
Oct 8, 2019
Oct 22, 2019
Jul 19, 2019
Aug 21, 2019
Jul 19, 2019
Oct 10, 2019
Jul 19, 2019
Aug 27, 2019
Jul 25, 2019
Oct 11, 2019
Sep 23, 2019

Repository files navigation

ARDaP - Antimicrobial Resistance Detection and Prediction

ARDaP was written by Derek Sarovich (@DerekSarovich) (University of the Sunshine Coast, Australia) with database construction, code testing and feature design by Danielle Madden (@dmadden9), Eike Steinig (@EikeSteinig) (Australian Institute of Tropical Health and Medicine, Australia) and Erin Price (@Dr_ErinPrice).

Contents

Introduction

ARDaP (Antimicrobial Resistance Detection and Prediction) is a genomics pipeline for the comprehensive identification of antibiotic resistance markers from whole-genome sequencing data. The impetus behind the creation of ARDaP was our frustration with current methodology not being able to detect antimicrobial resistance when confered by "complex" mechanisms. Our two species of interest, Burkholderia pseudomallei and Pseudomonas aeruginosa*, develop antimicrobial resistance in a multiple ways but predominately through chromosomal mutations, including gene loss, copy number variation, single nucleotide polymorphisms and indels. ARDaP will first identify all genetic variation in a sample and then interrogate this information against a user created database of resistance mechanisms. The software will then summarise the identified mechanisms and produce a simple report for the user.

*P. aeruginosa module is still under development

Installation

Short version for those that just want to get started and understand how environments in conda work

ARDaP is available on our development channel and its dependencies can be installed with:

conda install -c dsarov -c bioconda -c r ardap

The pipeline itself is run with Nextflow from a local cache of the repository:

nextflow run dsarov/ardap

The local cache can be updated with

nextflow pull dsarov/ardap

If you want to make changes to the default nextflow.config file clone the workflow into a local directory and change parameters in nextflow.config:

nextflow clone dsarov/ardap install_dir/

Or navigate to the conda install path of ARDaP and change the nextflow.config in that location.

Long version for those unfamiliar with environments or just want all the steps for recommended installation

  1. Make sure you have the conda package manager installed (e.g. Anaconda, miniconda). You can check this by testing if you can find the conda command (which conda). If you do have conda installed then it's a good idea to update conda so you have the latest version conda update conda. If you don't have this software installed then go to the miniconda install page and follow the instructions for your OS. After the install, make sure your install is up-to-date conda update conda.

  2. Create a new environment with conda called "ardap" and install the software with conda create --name ardap -c dsarov -c bioconda -c r ardap. Follow the instructions and the software should fully install with all dependencies.

  3. ARDaP requires Tex (specifically XeLaTeX) for compilation of the reports. If you don't have this compiler in your PATH or Tex installed on your system, you can follow the instructions here for installation (https://nbconvert.readthedocs.io/en/latest/install.html). On centOS you should be able to run sudo yum install texlive-xetex or on Ubuntu sudo apt-get install texlive-xetex. Once installed check that xelatex is in your PATH i.e. which xelatex. If this is still not in your PATH you can edit the nextflow.config file to manually point to the xelatex compiler by editing the line env.PATH="$PATH:/usr/local/texlive/2017/bin/x86_64-linux/"

  4. Activate the ardap environment that was installed by conda, conda activate ardap

  5. To run ARDaP, nextflow run dsarov/ardap.

Usage

To control the data pipeline, ARDaP is implemented in Nextflow. More information about Nextflow can be found here

ARDaP can be called from the command line through Nextflow. This will pull the current workflow into local storage. Any parameter in the configuration file nextflow.config can be changed on the command line via -- dashes, while Nextflow runtime parameters can be changed via - dash.

For example, to run Nextflow with the default cluster job submission template profile for PBS, and activate the mixture setting in ARDaP we can run:

nextflow run dsarov/ardap --executor pbs --mixtures

Resource Managers

ARDaP is written in the nextflow language and as such has support for most resource management systems.

List of schedulers and default template profiles in nextflow.config and can be selected when the pipeline is initiated with the --executor flag. For example, if you want to run ARDaP on a system with PBS, simply set --executor pbs when initialising ARDaP. Most popular resource managers are supported (e.g. sge, slurm) with the default configuration running on the local system.

If you need any more information about how to set your resource manager (e.g. memory, queue, account settings) see https://www.nextflow.io/docs/latest/executor.html

If you would like to just submit jobs to the resource manager queue without monitoring, then use of the screen or nohup command will allow you to run the pipeline process in the background and won't kill the pipline if the shell is terminated. Examples of nohup are included below.

ARDaP Workflow

To achieve high-quality variant calls, ARDaP incorporates the following programs into its workflow:

  • Burrows Wheeler Aligner (BWA) (doi: 10.1093/bioinformatics/btp324)

  • SAMTools (ref)

  • Picard (ref)

  • Genome Analysis Toolkit (GATK) (ref)

  • BEDTools (ref)

  • SNPEff (ref)

  • VCFtools (ref)

Parameters

Optional Parameter:
--mixtures Optionally perform within species mixtures analysis or metagenomic analysis for species of interest. Run ARDaP with the --mixtures flag for analysis with multiple strains and/or metagenomic data. Default=false

Example:

$ nextflow run dsarov/ardap --mixtures

--size ARDaP can optionally down-sample your read data to run through the pipeline quicker (integer value expected). Default=1000000, which roughly coresponds to a 50x coverage given a genome size of 6Mbp. To switch downsampling off, specify --size 0. Note that this option is switch off when mixture analysis is requested.

Example:

$ nextflow run dsarov/ardap --size 0 --mixtures

--phylogeny Use this flag if you would like a whole genome phylogeny or a combined and annotated variant file. Note that this may take a long time if you have a large number of isolates. Default=false

Example:

$ nextflow run dsarov/ardap --phylogeny

--database Use this flag to specify an ARDaP database that contains species specific resistance information. Note that you will also need to specify the correct reference file with --ref.

Currently there are databases available for: Pseudomonas aeruginosa --database Pseudomonas_aeruginosa_pao1 --ref Pa_PAO1 Burkholderia pseudomallei --database Burkholderia_pseudomallei_k96243 --ref k96243

For example:
nextflow run dsarov/ardap --database Pseudomonas_aeruginosa_pao1 --ref Pa_PAO1

If you don't want to constantly use the flags for different databases, all of these settings can be changed in the nextflow.config file if the default parameters aren't suitable.

--fastq ARDaP, by default, expects reads to be paired-end, Illumina data in the following format:

STRAIN_1.fastq.gz (first pair) 
STRAIN_2.fastq.gz (second pair)

Reads not in this format will be ignored unless you change the --fastq flag to match the read naming on your system.

Example:

If your reads are in the following format

STRAIN_1_sequence.fq.gz (first pair) 
STRAIN_2_sequence.fq.gz (second pair)

`nextflow run dsarov/ardap --fastq "*_{1,2}_sequence.fq.gz"

Database-creation

TO BE ADDED

Bugs!!

Please send bug reports to derek.sarovich@gmail.com or log them in the github issues tab

Please send bug reports to derek.sarovich@gmail.com.

About

Comprehensive resistance detection from WGS data

Resources

Stars

Watchers

Forks

Packages

No packages published