Giter Site home page Giter Site logo

nf-core / taxprofiler Goto Github PK

View Code? Open in Web Editor NEW
93.0 144.0 32.0 12.24 MB

Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data

Home Page: https://nf-co.re/taxprofiler

License: MIT License

HTML 1.14% Nextflow 98.86%
metagenomics profiling taxonomic-profiling shotgun nf-core nextflow workflow pipeline classification microbiome

taxprofiler's Introduction

nf-core/taxprofiler

GitHub Actions CI Status GitHub Actions Linting StatusAWS CICite with Zenodo nf-test

Nextflow run with conda run with docker run with singularity Launch on Seqera Platform

Get help on SlackFollow on TwitterFollow on MastodonWatch on YouTube

Cite Preprint

Introduction

nf-core/taxprofiler is a bioinformatics best-practice analysis pipeline for taxonomic classification and profiling of shotgun short- and long-read metagenomic data. It allows for in-parallel taxonomic identification of reads or taxonomic abundance estimation with multiple classification and profiling tools against multiple databases, and produces standardised output tables for facilitating results comparison between different tools and databases.

Pipeline summary

  1. Read QC (FastQC or falco as an alternative option)
  2. Performs optional read pre-processing
  3. Supports statistics for host-read removal (Samtools)
  4. Performs taxonomic classification and/or profiling using one or more of:
  5. Perform optional post-processing with:
  6. Standardises output tables (Taxpasta)
  7. Present QC for raw reads (MultiQC)
  8. Plotting Kraken2, Centrifuge, Kaiju and MALT results (Krona)

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.

First, prepare a samplesheet with your input data that looks as follows:

samplesheet.csv:

sample,run_accession,instrument_platform,fastq_1,fastq_2,fasta
2612,run1,ILLUMINA,2612_run1_R1.fq.gz,,
2612,run2,ILLUMINA,2612_run2_R1.fq.gz,,
2612,run3,ILLUMINA,2612_run3_R1.fq.gz,2612_run3_R2.fq.gz,

Each row represents a fastq file (single-end), a pair of fastq files (paired end), or a fasta (with long reads).

Additionally, you will need a database sheet that looks as follows:

databases.csv:

tool,db_name,db_params,db_path
kraken2,db2,--quick,/<path>/<to>/kraken2/testdb-kraken2.tar.gz
metaphlan,db1,,/<path>/<to>/metaphlan/metaphlan_database/

That includes directories or .tar.gz archives containing databases for the tools you wish to run the pipeline against.

Now, you can run the pipeline using:

nextflow run nf-core/taxprofiler \
   -profile <docker/singularity/.../institute> \
   --input samplesheet.csv \
   --databases databases.csv \
   --outdir <OUTDIR>  \
   --run_kraken2 --run_metaphlan

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.

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/taxprofiler was originally written by James A. Fellows Yates, Sofia Stamouli, Moritz E. Beber, and the nf-core/taxprofiler team.

Team

We thank the following people for their contributions to the development of this pipeline:

Acknowledgments

We also are grateful for the feedback and comments from:

And specifically to

❤️ also goes to Zandra Fagernäs for the logo.

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 #taxprofiler channel (you can join with this invite).

Citations

If you use nf-core/taxprofiler for your analysis, please cite it using the following doi: 10.1101/2023.10.20.563221.

Stamouli, S., Beber, M. E., Normark, T., Christensen II, T. A., Andersson-Li, L., Borry, M., Jamy, M., nf-core community, & Fellows Yates, J. A. (2023). nf-core/taxprofiler: Highly parallelised and flexible pipeline for metagenomic taxonomic classification and profiling. In bioRxiv (p. 2023.10.20.563221). https://doi.org/10.1101/2023.10.20.563221

For the latest version of the code, cite the Zenodo doi: 10.5281/zenodo.7728364

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.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.