bioinformatics-lab / mtbseq-nf

MTBSeq made simple and easy using Nextflow.

mtbseq-nf

mtbseq-nf pipeline makes MTBseq simple and easy to use via Nextflow workflow manager.

Benefits of the Nextflow wrapper

• Fine-grained control over resource allocation (CPU/Memory/Storage)
• Reliance of bioconda and biocontainers for installing packages for reproducibility
• Ease of use on a range of infrastructure (cloud/on-prem clusters/local machine)
• Resumability for failed processes
• Centralized locations for specifying
  • MTBseq parameters (conf/global_parameters.config)
  • Hardware requirements (conf/standard.config)
  • Software requirements (conf/docker.config or conf/conda.config)
• Dedicated user interface for all parameters for wider audience (nextflow_schema.json). This only works on Nextflow Tower.
• Easier customizability for the pipeline, using explicit parameters (conf/global_parameters.config).
• Ability to analyze genomes in parallel as well as in batch, on local, cloud and cluster environments.

Usage

The simplest use case is to analyze a few genomes on a local environment. Almost all aspects are customizable but for the sake of brevity, a bare bones guide for any beginner user is as shown below

• 1. Clone the project

git clone https://github.com/mtb-bioinformatics/mtbseq-nf
cd mtbseq-nf

• 2. Download the gatk-3.8.0 tar from here

• 3. Untar it and place it in the resources folder

tar -xvf GATK_TAR_FILE

• 4. Move your genomes to the data/full_data folder

They should follow the pattern SAMPLE_R1.fastq.gz

• 5. To run the pipeline, make sure you have conda installed. Moreover, if you don't already have nextflow installed, you can use the following commands to install it

conda create -n mtbseq-nf-env -c bioconda -c conda-forge nextflow 

You can confirm the setup by activating that environment and using the nextflow info command

conda activate -n mtbseq-nf-env

nextflow info 

• 6. Then simply issue the following command on the command line

nextflow run main.nf -profile standard,conda

Workflow example

This pipeline has two execution types: batch and parallel and here is a dag example for them!

The execution type is determined by the analysis_mode parameter

Batch

Parallel

Contributions

Contributions are warmly accepted!

License

The insipiration for this project itself MTBseq has a GPL-3 license as of v1.0.3.

The components related to mtbseq-nf project itself (the Nextflow wrapper code) are licensed under the liberal MPL-2.0 license.

We would like to Thank the developers of MTBseq for putting in the intial effort!