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createtaxdb

Parallelised and automated construction of metagenomic classifier databases of different tools

https://github.com/nf-core/createtaxdb

Science Score: 57.0%

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    Found 28 DOI reference(s) in README
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Keywords

database database-builder metagenomic-profiling metagenomics nextflow nf-core pipeline profiling taxonomic-profiling workflow
Last synced: 4 months ago · JSON representation ·

Repository

Parallelised and automated construction of metagenomic classifier databases of different tools

Basic Info
Statistics
  • Stars: 13
  • Watchers: 178
  • Forks: 9
  • Open Issues: 8
  • Releases: 1
Topics
database database-builder metagenomic-profiling metagenomics nextflow nf-core pipeline profiling taxonomic-profiling workflow
Created about 2 years ago · Last pushed 6 months ago
Metadata Files
Readme Changelog Contributing License Code of conduct Citation Codeowners

README.md

nf-core/createtaxdb

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

Nextflow nf-core template version run with conda run with docker run with singularity Launch on Seqera Platform

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Introduction

nf-core/createtaxdb is a bioinformatics pipeline that constructs custom metagenomic classifier databases for multiple classifiers and profilers from the same input reference genome set in a highly automated and parallelised manner. It supports both nucleotide and protein based classifiers and profilers. The pipeline is designed to be a companion pipeline to nf-core/taxprofiler for taxonomic profiling of metagenomic data, but can be used for any context.

nf-core/createtaxdb

  1. Prepares input FASTA files for building
  2. Builds databases for:

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 an input CSV table with your input reference genomes that looks as follows:

csv id,taxid,fasta_dna,fasta_aa Human_Mitochondrial_genome,9606,chrMT.fna, SARS-CoV-2_genome,694009,GCA_011545545.1_ASM1154554v1_genomic.fna.gz,GCA_011545545.1_ASM1154554v1_genomic.faa.gz Bacteroides_fragilis_genome,817,GCF_016889925.1_ASM1688992v1_genomic.fna.gz,GCF_016889925.1_ASM1688992v1_genomic.faa.gz Candidatus_portiera_aleyrodidarum_genome,91844,GCF_000292685.1_ASM29268v1_genomic.fna,GCF_000292685.1_ASM29268v1_genomic.faa Haemophilus_influenzae_genome,727,GCF_900478275.1_34211_D02_genomic.fna,GCF_900478275.1_34211_D02_genomic.faa Streptococcus_agalactiae_genome,1311,,GCF_002881355.1_ASM288135v1_genomic.faa

Each row contains a human readable name, the taxonomic ID of the organism, and then an (optionally gzipped) Nucleotide and/or Amino Acid FASTA file.

Now, with an appropriate set of taxonomy files you can build databases for multiple profilers - such as Kraken2, ganon, and DIAMOND - in parallel:

bash nextflow run nf-core/createtaxdb \ -profile <docker/singularity/.../institute> \ --input samplesheet.csv \ --accession2taxid /<path>/<to>/taxonomy/nucl_gb.accession2taxid \ --nucl2taxid /<path>/<to>/taxonomy/nucl.accession2taxid.gz \ --prot2taxid /<path>/<to>/taxonomy/prot.accession2taxid.gz \ --nodesdmp /<path>/<to>/taxonomy/nodes.dmp \ --namesdmp /<path>/<to>/taxonomy/names.dmp \ --build_kraken2 \ --kraken2_build_options='--kmer-len 45' \ --build_ganon \ --ganon_build_options='--kmer-size 45' \ --build_diamond \ --diamond_build_options='--no-parse-seqids' \ --outdir <OUTDIR>

The output directory will contain directories containing the database files for each of the profilers you selected to build. Optionally you can also package these as tar.gz archives.

You can also generate pre-prepared input sheets for database specifications of pipelines such as nf-core/taxprofiler using --generate_downstream_samplesheets.

[!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/createtaxdb was originally written by James A. Fellows Yates, Sam Wilkinson, Alexander Ramos Díaz, Lili Andersson-Li and the nf-core community.

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

  • Zandra Fagernäs for logo design

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

Citations

If you use nf-core/createtaxdb for your analysis, please cite it using the following doi: 10.5281/zenodo.15696114

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.

Owner

  • Name: nf-core
  • Login: nf-core
  • Kind: organization
  • Email: core@nf-co.re

A community effort to collect a curated set of analysis pipelines built using Nextflow.

Citation (CITATIONS.md) 

# nf-core/createtaxdb: Citations

## [nf-core](https://pubmed.ncbi.nlm.nih.gov/32055031/)

> Ewels PA, Peltzer A, Fillinger S, Patel H, Alneberg J, Wilm A, Garcia MU, Di Tommaso P, Nahnsen S. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020 Mar;38(3):276-278. doi: 10.1038/s41587-020-0439-x. PubMed PMID: 32055031.

## [Nextflow](https://pubmed.ncbi.nlm.nih.gov/28398311/)

> Di Tommaso P, Chatzou M, Floden EW, Barja PP, Palumbo E, Notredame C. Nextflow enables reproducible computational workflows. Nat Biotechnol. 2017 Apr 11;35(4):316-319. doi: 10.1038/nbt.3820. PubMed PMID: 28398311.

## Pipeline tools

- [MultiQC](https://pubmed.ncbi.nlm.nih.gov/27312411/)

  > Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016 Oct 1;32(19):3047-8. doi: 10.1093/bioinformatics/btw354. Epub 2016 Jun 16. PubMed PMID: 27312411; PubMed Central PMCID: PMC5039924.

## Software packaging/containerisation tools

- [Anaconda](https://anaconda.com)

  > Anaconda Software Distribution. Computer software. Vers. 2-2.4.0. Anaconda, Nov. 2016. Web.

- [Bioconda](https://pubmed.ncbi.nlm.nih.gov/29967506/)

  > Grüning B, Dale R, Sjödin A, Chapman BA, Rowe J, Tomkins-Tinch CH, Valieris R, Köster J; Bioconda Team. Bioconda: sustainable and comprehensive software distribution for the life sciences. Nat Methods. 2018 Jul;15(7):475-476. doi: 10.1038/s41592-018-0046-7. PubMed PMID: 29967506.

- [BioContainers](https://pubmed.ncbi.nlm.nih.gov/28379341/)

  > da Veiga Leprevost F, Grüning B, Aflitos SA, Röst HL, Uszkoreit J, Barsnes H, Vaudel M, Moreno P, Gatto L, Weber J, Bai M, Jimenez RC, Sachsenberg T, Pfeuffer J, Alvarez RV, Griss J, Nesvizhskii AI, Perez-Riverol Y. BioContainers: an open-source and community-driven framework for software standardization. Bioinformatics. 2017 Aug 15;33(16):2580-2582. doi: 10.1093/bioinformatics/btx192. PubMed PMID: 28379341; PubMed Central PMCID: PMC5870671.

- [Docker](https://dl.acm.org/doi/10.5555/2600239.2600241)

  > Merkel, D. (2014). Docker: lightweight linux containers for consistent development and deployment. Linux Journal, 2014(239), 2. doi: 10.5555/2600239.2600241.

- [Singularity](https://pubmed.ncbi.nlm.nih.gov/28494014/)

  > Kurtzer GM, Sochat V, Bauer MW. Singularity: Scientific containers for mobility of compute. PLoS One. 2017 May 11;12(5):e0177459. doi: 10.1371/journal.pone.0177459. eCollection 2017. PubMed PMID: 28494014; PubMed Central PMCID: PMC5426675.

- [Bracken](https://doi.org/10.7717/peerj-cs.104)

  > Lu, J., Breitwieser, F. P., Thielen, P., & Salzberg, S. L. (2017). Bracken: estimating species abundance in metagenomics data. PeerJ. Computer Science, 3(e104), e104. https://doi.org/10.7717/peerj-cs.104

- [Centrifuge](https://doi.org/10.1101/gr.210641.116)

  > Kim, D., Song, L., Breitwieser, F. P., & Salzberg, S. L. (2016). Centrifuge: rapid and sensitive classification of metagenomic sequences. Genome Research, 26(12), 1721–1729. https://doi.org/10.1101/gr.210641.116

- [DIAMOND](https://doi.org/10.1038/nmeth.3176)

  > Buchfink, B., Xie, C., & Huson, D. H. (2015). Fast and sensitive protein alignment using DIAMOND. Nature Methods, 12(1), 59–60. https://doi.org/10.1038/nmeth.3176

- [ganon](https://doi.org/10.1093/bioinformatics/btaa458)

  > Piro, V. C., Dadi, T. H., Seiler, E., Reinert, K., & Renard, B. Y. (2020). Ganon: Precise metagenomics classification against large and up-to-date sets of reference sequences. Bioinformatics (Oxford, England), 36(Suppl_1), i12–i20. https://doi.org/10.1093/bioinformatics/btaa458

- [Kaiju](https://doi.org/10.1038/ncomms11257)

> Menzel, P., Ng, K. L., & Krogh, A. (2016). Fast and sensitive taxonomic classification for metagenomics with Kaiju. Nature Communications, 7, 11257. https://doi.org/10.1038/ncomms11257

- [KMCP](https://doi.org/10.1093/bioinformatics/btac845)

  > Shen, W., Xiang, H., Huang, T., Tang, H., Peng, M., Cai, D., Hu, P., & Ren, H. (2023). KMCP: accurate metagenomic profiling of both prokaryotic and viral populations by pseudo-mapping. Bioinformatics (Oxford, England), 39(1). https://doi.org/10.1093/bioinformatics/btac845

- [Kraken2](https://doi.org/10.1186/s13059-019-1891-0)

  > Wood, D. E., Lu, J., & Langmead, B. (2019). Improved metagenomic analysis with Kraken 2. Genome Biology, 20(1), 257. https://doi.org/10.1186/s13059-019-1891-0

- [KrakenUniq](https://doi.org/10.1186/s13059-018-1568-0)

  > Breitwieser, F. P., Baker, D. N., & Salzberg, S. L. (2018). KrakenUniq: confident and fast metagenomics classification using unique k-mer counts. Genome Biology, 19(1), 198. https://doi.org/10.1186/s13059-018-1568-0

- [MALT](https://doi.org/10.1038/s41559-017-0446-6)

  > Vågene, Å. J., Herbig, A., Campana, M. G., Robles García, N. M., Warinner, C., Sabin, S., Spyrou, M. A., Andrades Valtueña, A., Huson, D., Tuross, N., Bos, K. I., & Krause, J. (2018). Salmonella enterica genomes from victims of a major sixteenth-century epidemic in Mexico. Nature Ecology & Evolution, 2(3), 520–528. https://doi.org/10.1038/s41559-017-0446-6

- [SeqKit2](https://doi.org/10.1002/imt2.191)

> Shen, W., Sipos, B., & Zhao, L. (2024). SeqKit2: A Swiss army knife for sequence and alignment processing. iMeta, e191. https://doi.org/10.1002/imt2.191

GitHub Events

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Last Year
  • Issues event: 32
  • Watch event: 6
  • Delete event: 26
  • Issue comment event: 128
  • Push event: 189
  • Pull request event: 64
  • Pull request review comment event: 90
  • Pull request review event: 107
  • Fork event: 5
  • Create event: 25

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 21
  • Total pull requests: 34
  • Average time to close issues: 6 months
  • Average time to close pull requests: 14 days
  • Total issue authors: 3
  • Total pull request authors: 4
  • Average comments per issue: 0.9
  • Average comments per pull request: 1.62
  • Merged pull requests: 24
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 16
  • Pull requests: 34
  • Average time to close issues: 2 months
  • Average time to close pull requests: 14 days
  • Issue authors: 3
  • Pull request authors: 4
  • Average comments per issue: 0.69
  • Average comments per pull request: 1.62
  • Merged pull requests: 24
  • Bot issues: 0
  • Bot pull requests: 0
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Top Authors
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  • jfy133 (34)
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Pull Request Authors
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  • nf-core-bot (12)
  • alxndrdiaz (4)
  • BioWilko (2)
  • LilyAnderssonLee (1)
Top Labels
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Dependencies

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.github/workflows/clean-up.yml actions
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.github/workflows/fix-linting.yml actions
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.github/workflows/linting.yml actions
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.github/workflows/linting_comment.yml actions
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.github/workflows/release-announcments.yml actions
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  • zentered/bluesky-post-action v0.0.2 composite
modules/nf-core/custom/dumpsoftwareversions/meta.yml cpan
modules/nf-core/fastqc/meta.yml cpan
modules/nf-core/multiqc/meta.yml cpan
pyproject.toml pypi