Introduction

metaXplore is a modular bioinformatics pipeline to conduct basic, rapid data exploration of metagenomic sequencing data at a glance.

The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The Nextflow DSL2 implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies. Where possible, these processes have been installed from nf-core/modules. On release, automated continuous integration tests run the pipeline on a full-sized dataset on the AWS cloud infrastructure. This ensures that the pipeline runs on AWS, has sensible resource allocation defaults set to run on real-world datasets, and permits the persistent storage of results to benchmark between pipeline releases and other analysis sources.

Pipeline summary

1. Read QC (FastQC)
2. Trim/QC raw reads with Fastp (Fastp)
3. Estimate metagenome coverage and diversity with Nonpareil (Nonpareil)
4. Classify QC'd reads with classifier of your choice (curently either (Kraken2) or (Metaphlan3). Kraken2 classifications can be further refined with (Bracken))
5. Visualize taxonomic profiles using (Krona)
6. Present QC and stats for reads and taxonomic profiles (MultiQC)

Please note that inclusion of Bracken is still a work-in-progress. Use it at your discretion. Kraken2 and Metaphlan tracks should work out of the box.

Quick Start

1. Install Nextflow (>=21.10.1)

2. Install any of Docker, Singularity (you can follow this tutorial), Podman, Shifter or Charliecloud for full pipeline reproducibility (you can use Conda both to install Nextflow itself and also to manage software within pipelines. Please only use it within pipelines as a last resort; see docs).

3. Download the pipeline and test it on a minimal dataset with a single command:

   nextflow run hseabolt/metaxplore -profile test,YOURPROFILE --outdir <OUTDIR>

   Note that some form of configuration will be needed so that Nextflow knows how to fetch the required software. This is usually done in the form of a config profile (YOURPROFILE in the example command above). You can chain multiple config profiles in a comma-separated string.

   • The pipeline comes with config profiles called docker, singularity, podman, shifter, charliecloud and conda which instruct the pipeline to use the named tool for software management. For example, -profile test,docker.
   • Please check nf-core/configs to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use -profile <institute> in your command. This will enable either docker or singularity and set the appropriate execution settings for your local compute environment.
   • If you are using singularity, please use the nf-core download command to download images first, before running the pipeline. Setting the NXF_SINGULARITY_CACHEDIR or singularity.cacheDir Nextflow options enables you to store and re-use the images from a central location for future pipeline runs.
   • If you are using conda, it is highly recommended to use the NXF_CONDA_CACHEDIR or conda.cacheDir settings to store the environments in a central location for future pipeline runs.

4. Start running your own analysis!

   nextflow run hseabolt/metaxplore --input samplesheet.csv --outdir <OUTDIR> --classifier <kraken2|metaphlan4> --db <DB> -profile <docker/singularity/podman/shifter/charliecloud/conda/institute>

Credits

metaXplore was originally written by Matthew H. Seabolt (Github: @hseabolt).

Contributions and Support

I welcome collaborative contributions and suggestions to expand the utility of this workflow, which will be explored on as-available basis.

Citations

If you use hseabolt/metaxplore for your analysis, please cite it using the following doi: 10.5281/zenodo.1400710

An extensive list of references for the tools used by the pipeline can be found in the CITATIONS.md file.

This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT license.

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.