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150 lines
8.3 KiB
Markdown
150 lines
8.3 KiB
Markdown
# ![nf-core/taxprofiler](docs/images/nf-core-taxprofiler_logo_custom_light.png#gh-light-mode-only) ![nf-core/taxprofiler](docs/images/nf-core-taxprofiler_logo_custom_dark.png#gh-dark-mode-only)
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[![AWS CI](https://img.shields.io/badge/CI%20tests-full%20size-FF9900?labelColor=000000&logo=Amazon%20AWS)](https://nf-co.re/taxprofiler/results)[![Cite with Zenodo](http://img.shields.io/badge/DOI-10.5281/zenodo.XXXXXXX-1073c8?labelColor=000000)](https://doi.org/10.5281/zenodo.XXXXXXX)
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[![Nextflow](https://img.shields.io/badge/nextflow%20DSL2-%E2%89%A522.10.1-23aa62.svg)](https://www.nextflow.io/)
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[![run with conda](http://img.shields.io/badge/run%20with-conda-3EB049?labelColor=000000&logo=anaconda)](https://docs.conda.io/en/latest/)
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[![run with docker](https://img.shields.io/badge/run%20with-docker-0db7ed?labelColor=000000&logo=docker)](https://www.docker.com/)
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[![run with singularity](https://img.shields.io/badge/run%20with-singularity-1d355c.svg?labelColor=000000)](https://sylabs.io/docs/)
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[![Launch on Nextflow Tower](https://img.shields.io/badge/Launch%20%F0%9F%9A%80-Nextflow%20Tower-%234256e7)](https://tower.nf/launch?pipeline=https://github.com/nf-core/taxprofiler)
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[![Get help on Slack](http://img.shields.io/badge/slack-nf--core%20%23taxprofiler-4A154B?labelColor=000000&logo=slack)](https://nfcore.slack.com/channels/taxprofiler)[![Follow on Twitter](http://img.shields.io/badge/twitter-%40nf__core-1DA1F2?labelColor=000000&logo=twitter)](https://twitter.com/nf_core)[![Follow on Mastodon](https://img.shields.io/badge/mastodon-nf__core-6364ff?labelColor=FFFFFF&logo=mastodon)](https://mstdn.science/@nf_core)[![Watch on YouTube](http://img.shields.io/badge/youtube-nf--core-FF0000?labelColor=000000&logo=youtube)](https://www.youtube.com/c/nf-core)
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## Introduction
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**nf-core/taxprofiler** is a bioinformatics best-practice analysis pipeline for taxonomic classification and profiling of shotgun 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, produces standardised output tables.
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## Pipeline summary
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![](docs/images/taxprofiler_tube.png)
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1. Read QC ([`FastQC`](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) or [`falco`](https://github.com/smithlabcode/falco) as an alternative option)
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2. Performs optional read pre-processing
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- Adapter clipping and merging (short-read: [fastp](https://github.com/OpenGene/fastp), [AdapterRemoval2](https://github.com/MikkelSchubert/adapterremoval); long-read: [porechop](https://github.com/rrwick/Porechop))
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- Low complexity and quality filtering (short-read: [bbduk](https://jgi.doe.gov/data-and-tools/software-tools/bbtools/), [PRINSEQ++](https://github.com/Adrian-Cantu/PRINSEQ-plus-plus); long-read: [Filtlong](https://github.com/rrwick/Filtlong))
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- Host-read removal (short-read: [BowTie2](http://bowtie-bio.sourceforge.net/bowtie2/); long-read: [Minimap2](https://github.com/lh3/minimap2))
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- Run merging
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3. Supports statistics for host-read removal ([Samtools](http://www.htslib.org/))
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4. Performs taxonomic classification and/or profiling using one or more of:
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- [Kraken2](https://ccb.jhu.edu/software/kraken2/)
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- [MetaPhlAn3](https://huttenhower.sph.harvard.edu/metaphlan/)
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- [MALT](https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/algorithms-in-bioinformatics/software/malt/)
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- [DIAMOND](https://github.com/bbuchfink/diamond)
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- [Centrifuge](https://ccb.jhu.edu/software/centrifuge/)
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- [Kaiju](https://kaiju.binf.ku.dk/)
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- [mOTUs](https://motu-tool.org/)
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- [KrakenUniq](https://github.com/fbreitwieser/krakenuniq)
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5. Perform optional post-processing with:
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- [bracken](https://ccb.jhu.edu/software/bracken/)
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6. Standardises output tables ([`Taxpasta`](https://taxpasta.readthedocs.io))
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7. Present QC for raw reads ([`MultiQC`](http://multiqc.info/))
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8. Plotting Kraken2, Centrifuge, Kaiju and MALT results ([`Krona`](https://hpc.nih.gov/apps/kronatools.html))
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## Usage
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> **Note**
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> If you are new to Nextflow and nf-core, please refer to [this page](https://nf-co.re/docs/usage/installation) on how
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> to set-up Nextflow. Make sure to [test your setup](https://nf-co.re/docs/usage/introduction#how-to-run-a-pipeline)
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> with `-profile test` before running the workflow on actual data.
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First, prepare a samplesheet with your input data that looks as follows:
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`samplesheet.csv`:
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```csv
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sample,run_accession,instrument_platform,fastq_1,fastq_2,fasta
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2612,run1,ILLUMINA,2612_run1_R1.fq.gz,,
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2612,run2,ILLUMINA,2612_run2_R1.fq.gz,,
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2612,run3,ILLUMINA,2612_run3_R1.fq.gz,2612_run3_R2.fq.gz,
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```
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Each row represents a fastq file (single-end), a pair of fastq files (paired end), or a fasta (with long reads).
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Additionally, you will need a database sheet that looks as follows:
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`databases.csv`:
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```
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tool,db_name,db_params,db_path
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kraken2,db2,--quick,/<path>/<to>/kraken2/testdb-kraken2.tar.gz
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metaphlan3,db1,,/<path>/<to>/metaphlan3/metaphlan_database/
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```
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That includes directories or `.tar.gz` archives containing databases for the tools you wish to run the pipeline against.
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Now, you can run the pipeline using:
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```bash
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nextflow run nf-core/taxprofiler \
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-profile <docker/singularity/.../institute> \
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--input samplesheet.csv \
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--databases databases.csv \
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--outdir <OUTDIR> \
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--run_kraken2 --run_metaphlan3
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```
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> **Warning:**
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> Please provide pipeline parameters via the CLI (as above) or Nextflow `-params-file` option. Custom config files including those
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> provided by the `-c` Nextflow option can be used to provide any configuration _**except for parameters**_;
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> see [docs](https://nf-co.re/usage/configuration#custom-configuration-files).
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For more details, please refer to the [usage documentation](https://nf-co.re/taxprofiler/usage) and the [parameter documentation](https://nf-co.re/taxprofiler/parameters).
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## Pipeline output
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To see the results of a test run with a full size dataset refer to the [results](https://nf-co.re/taxprofiler/results) tab on the nf-core website pipeline page.
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For more details about the output files and reports, please refer to the
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[output documentation](https://nf-co.re/taxprofiler/output).
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## Credits
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nf-core/taxprofiler was originally written by James A. Fellows Yates, Sofia Stamouli, Moritz E. Beber, and the nf-core/taxprofiler team.
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### Team
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- [James A. Fellows Yates](https://github.com/jfy133)
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- [Sofia Stamouli](https://github.com/sofstam)
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- [Moritz E. Beber](https://github.com/Midnighter)
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We thank the following people for their contributions to the development of this pipeline:
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- [Lauri Mesilaakso](https://github.com/ljmesi)
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- [Tanja Normark](https://github.com/talnor)
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- [Maxime Borry](https://github.com/maxibor)
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- [Thomas A. Christensen II](https://github.com/MillironX)
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- [Jianhong Ou](https://github.com/jianhong)
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- [Rafal Stepien](https://github.com/rafalstepien)
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- [Mahwash Jamy](https://github.com/mjamy)
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### Acknowledgments
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We also are grateful for the feedback and comments from:
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- The general [nf-core/community](https://nf-co.re/community)
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And specifically to
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- [Alex Hübner](https://github.com/alexhbnr)
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- [Lily Andersson Lee](https://github.com/LilyAnderssonLee)
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❤️ also goes to [Zandra Fagernäs](https://github.com/ZandraFagernas) for the logo.
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## Contributions and Support
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If you would like to contribute to this pipeline, please see the [contributing guidelines](.github/CONTRIBUTING.md).
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For further information or help, don't hesitate to get in touch on the [Slack `#taxprofiler` channel](https://nfcore.slack.com/channels/taxprofiler) (you can join with [this invite](https://nf-co.re/join/slack)).
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## Citations
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If you use nf-core/taxprofiler for your analysis, please cite it using the following doi: [10.5281/zenodo.7728364](https://doi.org/10.5281/zenodo.7728364)
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An extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file.
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You can cite the `nf-core` publication as follows:
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> **The nf-core framework for community-curated bioinformatics pipelines.**
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>
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> Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.
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>
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> _Nat Biotechnol._ 2020 Feb 13. doi: [10.1038/s41587-020-0439-x](https://dx.doi.org/10.1038/s41587-020-0439-x).
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