Introduction

sanger-tol/sequencecomposition is a bioinformatics analysis pipeline that extracts statistics from a genome about its sequence composition.

The pipeline takes an assembly Fasta file (possibly compressed), runs fasta_windows on it, and transforms the outputs into files more practical for downstream use.

Steps involved:

• Run fasta_windows on the assembly Fasta file.
• Extract single-statistics bedGraph files from the multi-statistics TSV files fasta_windows outputs.
• Compress and index all bedGraph and TSV files with bgzip and tabix.

Usage

Note If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data.

The easiest is to provide the path of the Fasta file to analyse like this:

nextflow run sanger-tol/sequencecomposition --fasta /path/to/genome.fa

Warning: Please provide pipeline parameters via the CLI or Nextflow -params-file option. Custom config files including those provided by the -c Nextflow option can be used to provide any configuration except for parameters; see docs.

The pipeline also supports bulk downloads through a sample-sheet. More information about this mode on our pipeline website.

Credits

sanger-tol/sequencecomposition was originally written by Matthieu Muffato.

We thank the following people for their assistance in the development of this pipeline:

• Priyanka Surana for providing reviews.
• Tyler Chafin for updates.

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 #pipelines channel. Please create an issue on GitHub if you are not on the Sanger slack channel.

Citations

If you use sanger-tol/sequencecomposition for your analysis, please cite it using the following doi: 10.5281/zenodo.14358108

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.