nf-core/magmap

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Introduction

nf-core/magmap is a bioinformatics best-practice analysis pipeline for mapping reads to a (large) collections of genomes.

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 submitted to and installed from nf-core/modules in order to make them available to all nf-core pipelines, and to everyone within the Nextflow community!

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.The results obtained from the full-sized test can be viewed on the nf-core website.

Pipeline summary

1. Read QC (FastQC)
2. Present QC for raw reads (MultiQC)
3. Quality trimming and adapters removal for raw reads (Trimm Galore!)
4. Filter reads with BBduk
5. Select reference genomes based on k-mer signatures in reads with SOURMASH
6. Quantification of genes identified in selected reference genomes:
   1. generate index of assembly (BBmap index)
   2. Mapping cleaned reads to the assembly for quantification (BBmap)
   3. Get raw counts per each gene present in the genomes (Featurecounts) -> TSV table with collected featurecounts output
7. Choice of functional annotation:
   1. Eggnog-mapper
   2. kofamscan
   3. Hmmsearch. Besides searching the ORFs, each ORF’s hits will be ranked.
8. Summary statistics table. Collect_stats.R

Usage

Now, you can run the pipeline using:

nextflow run nf-core/magmap --input samplesheet.csv --reference_csv reference_genomes.csv --outdir <OUTDIR> -profile <docker/singularity/podman/shifter/charliecloud/conda/institute>

For more details and further functionality, please refer to the usage documentation and the parameter documentation.

Pipeline output

To see the results of an example test run with a full size dataset refer to the results tab on the nf-core website pipeline page. For more details about the output files and reports, please refer to the output documentation.

Credits

nf-core/magmap was originally written by Danilo Di Leo @danilodileo, Emelie Nilsson @emnillson and Daniel Lundin @erikrikardaniel.

Contributions and Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

For further information or help, don’t hesitate to get in touch on the Slack #magmap channel (you can join with this invite).

Citations

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

You can cite the nf-core publication as follows:

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.