Bactocap: Anthrax and Mycoplasma

Target-enrichment sequencing yields valuable genomic data for difficult-to-culture bacteria of public health importance

This repo contains all the materials required to reproduce the analysis and workflow from the targeted sequence capture project in Dennis et al, 2022, see:https://doi.org/10.1101/2022.02.16.480634

Getting started

This project uses Docker to manage all the dependencies, and nextflow to run the analysis. To get started, make sure you have docker installed. Installation instructions by platform are here: https://docs.docker.com/engine/install/ . Once you're finished, fire up the terminal and doublecheck with docker -v Then, install nextflow: https://www.nextflow.io/docs/latest/getstarted.html . And check in the terminal again to make sure it runs ok.

Setup and Docker installations

Clone the repo

git clone https://github.com/tristanpwdennis/bactocap.git

Enter the repo cd bactocap

Now we need to build the custom Docker image for this project, and also download the GATK Docker image. This command will build the dennistpw/align Docker image. This will take a few minutes.

DOCKER_BUILDKIT=1 docker build -t dennistpw/align --no-cache . 

Next we need to pull the GATK docker image

docker pull broadinstitute/gatk

Now let's check to make sure both of the images are ok

docker images

You should see the gatk and align repos are in the list.

Data

The raw data are located at PRJEB46822 (B. anthracis) and PRJEB50216 (M. amphoriforme). Download the raw reads into the corresponding dataset/organism/raw_read directories.

Running the workflow

It's as simple as running

nextflow run main.nf --help

This will prompt the USAGE statement and some brief pointers.

===================================================================
This is the BACTOCAP pipeline (VERSION)                        
===================================================================
The BACTOCAP workflow will run on whichever dataset is passed as an argument as shown below. 

USAGE: 

nextflow run main.nf --dataset <dataset>

Arguments:
   --dataset  STRING: anthrax, mycoplasma  (e.g. --organism anthrax)  Pick whether to run BACTOCAP on anthrax, or mycoplasma datasets

====================================================================

Nextflow caches all the steps, so you don't have to go back to square one with each reanalysis. Just add more data to the raw_reads directory, or restart if you accidentally shut off your machine with

nextflow run main.nf -resume

Note, I quite like running these scripts in screen sessions: https://linuxize.com/post/how-to-use-linux-screen/ This allows me to run the workflow, check on it periodically as it runs on the other screen, whilst I tool about doing other stuff. It also reduces the likelihood of that scenario where you accidentally close your laptop when you have a terminal session running and halt your analysis - TD

Output

The final bam files and mapping/sequencing stats will be published in the results directory in each dataset directory according to sample name The individual fastqc and bamqc data will be published in the individual_reports subdirectory and agglomerated in the multiqc_report.html document. A tab delimited text file mapping_stats.csv contains the flagstat data for analysis etc.

Analysis

Running the Rscript generate_bactocap_metadata.R will take the mapping output and parse it into a CSV containing sample metadata, mapping, duplicate and coverage information for anthrax and mycoplasma. Running Rscript bcanalysisfull.R will generate plots and tables in the figures_and_tables directory. Model output can be examined interactively in RStudio.

Pointers

Annotations and metadata are located in the ancillary directory. Reference genomes are contained in organism-specific directories under datasets