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nf-core/createtaxdb: Citations

nf-core

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

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

  • Bracken

    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

    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

    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

    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

    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

    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

    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

    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

    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

  • MetaCache

    Müller, A., Hundt, C., Hildebrandt, A., Hankeln, T., & Schmidt, B. (2017). MetaCache: context-aware classification of metagenomic reads using minhashing. Bioinformatics (Oxford, England), 33(23), 3740–3748. https://doi.org/10.1093/bioinformatics/btx520

  • MultiQC

    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.

  • SeqKit2

    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

  • sourmash

    Irber, L., Pierce-Ward, N. T., Abuelanin, M., Alexander, H., Anant, A., Barve, K., Baumler, C., Botvinnik, O., Brooks, P., Dsouza, D., Gautier, L., Hera, M. R., Houts, H. E., Johnson, L. K., Klötzl, F., Koslicki, D., Lim, M., Lim, R., Nelson, B., ... Brown, C. T. (2024). sourmash v4: A multitool to quickly search, compare,and analyze genomic and metagenomic data sets. Journal of Open Source Software, 9(98), 6830. https://doi.org/10.21105/joss.06830

  • sylph

Shaw, J., & Yu, Y. W. (2024). Rapid species-level metagenome profiling and containment estimation with sylph. Nature Biotechnology, 1–12. https://doi.org/10.1038/s41587-024-02412-y

Software packaging/containerisation tools

  • Anaconda

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

  • Bioconda

    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

    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.

  • conda-forge

    conda-forge community. (2015). The conda-forge Project: Community-based Software Distribution Built on the conda Package Format and Ecosystem. Zenodo. https://doi.org/10.5281/zenodo.4774217

  • Docker

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

  • Singularity

    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.