# nf-core/taxprofiler: 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 - [FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) - [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. - [falco](https://doi.org/10.12688/f1000research.21142.2) > de Sena Brandine G and Smith AD. Falco: high-speed FastQC emulation for quality control of sequencing data. F1000Research 2021, 8:1874 - [fastp](https://doi.org/10.1093/bioinformatics/bty560) > Chen, Shifu, Yanqing Zhou, Yaru Chen, and Jia Gu. 2018. Fastp: An Ultra-Fast All-in-One FASTQ Preprocessor. Bioinformatics 34 (17): i884-90. 10.1093/bioinformatics/bty560. - [AdapterRemoval2](https://doi.org/10.1186/s13104-016-1900-2) > Schubert, Mikkel, Stinus Lindgreen, and Ludovic Orlando. 2016. AdapterRemoval v2: Rapid Adapter Trimming, Identification, and Read Merging. BMC Research Notes 9 (February): 88. doi:10.1186/s13104-016-1900-2. - [Porechop](https://github.com/rrwick/Porechop) - [FILTLONG](https://github.com/rrwick/Filtlong) - [BBTools](http://sourceforge.net/projects/bbmap/) - [PRINSEQ++](https://doi.org/10.7287/peerj.preprints.27553v1) > Cantu, Vito Adrian, Jeffrey Sadural, and Robert Edwards. 2019. PRINSEQ++, a Multi-Threaded Tool for Fast and Efficient Quality Control and Preprocessing of Sequencing Datasets. e27553v1. PeerJ Preprints. doi: 10.7287/peerj.preprints.27553v1. - [Bowtie2](https://doi.org/10.1038/nmeth.1923) > Langmead, B., & Salzberg, S. L. (2012). Fast gapped-read alignment with Bowtie 2. Nature Methods, 9(4), 357–359. doi: 10.1038/nmeth.1923 - [minimap2](https://doi.org/10.1093/bioinformatics/bty191) > Li, H. (2018). Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics , 34(18), 3094–3100. doi: 10.1093/bioinformatics/bty191 - [SAMTools](https://doi.org/10.1093/gigascience/giab008) > Danecek, P., Bonfield, J. K., Liddle, J., Marshall, J., Ohan, V., Pollard, M. O., Whitwham, A., Keane, T., McCarthy, S. A., Davies, R. M., & Li, H. (2021). Twelve years of SAMtools and BCFtools. GigaScience, 10(2). doi: 10.1093/gigascience/giab008 - [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. doi: 10.7717/peerj-cs.104 - [Kraken2](https://doi.org/10.1186/s13059-019-1891-0) > Wood, Derrick E., Jennifer Lu, and Ben Langmead. 2019. Improved Metagenomic Analysis with Kraken 2. Genome Biology 20 (1): 257. doi: 10.1186/s13059-019-1891-0. - [KrakenUniq](https://doi.org/10.1186/s13059-018-1568-0) > Breitwieser, Florian P., Daniel N. Baker, and Steven L. Salzberg. 2018. KrakenUniq: confident and fast metagenomics classification using unique k-mer counts. Genome Biology 19 (1): 198. doi: 10.1186/s13059-018-1568-0 - [MetaPhlAn3](https://doi.org/10.7554/eLife.65088) > Beghini, Francesco, Lauren J McIver, Aitor Blanco-Míguez, Leonard Dubois, Francesco Asnicar, Sagun Maharjan, Ana Mailyan, et al. 2021. “Integrating Taxonomic, Functional, and Strain-Level Profiling of Diverse Microbial Communities with BioBakery 3.” Edited by Peter Turnbaugh, Eduardo Franco, and C Titus Brown. ELife 10 (May): e65088. doi: 10.7554/eLife.65088 - [MALT](https://doi.org/10.1038/s41559-017-0446-6) > Vågene, Åshild J., Alexander Herbig, Michael G. Campana, Nelly M. Robles García, Christina Warinner, Susanna Sabin, Maria A. Spyrou, et al. 2018. Salmonella Enterica Genomes from Victims of a Major Sixteenth-Century Epidemic in Mexico. Nature Ecology & Evolution 2 (3): 520-28. doi: 10.1038/s41559-017-0446-6. - [MEGAN](https://doi.org/10.1371/journal.pcbi.1004957) > Huson, Daniel H., Sina Beier, Isabell Flade, Anna Górska, Mohamed El-Hadidi, Suparna Mitra, Hans-Joachim Ruscheweyh, and Rewati Tappu. 2016. “MEGAN Community Edition - Interactive Exploration and Analysis of Large-Scale Microbiome Sequencing Data.” PLoS Computational Biology 12 (6): e1004957. doi: 10.1371/journal.pcbi.1004957. - [DIAMOND](https://doi.org/10.1038/nmeth.3176) > Buchfink, Benjamin, Chao Xie, and Daniel H. Huson. 2015. “Fast and Sensitive Protein Alignment Using DIAMOND.” Nature Methods 12 (1): 59-60. doi: 10.1038/nmeth.3176. - [Centrifuge](https://doi.org/10.1101/gr.210641.116) > Kim, Daehwan, Li Song, Florian P. Breitwieser, and Steven L. Salzberg. 2016. “Centrifuge: Rapid and Sensitive Classification of Metagenomic Sequences.” Genome Research 26 (12): 1721-29. doi: 10.1101/gr.210641.116. - [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. doi: 10.1038/ncomms11257 - [mOTUs](https://doi.org/10.1186/s40168-022-01410-z) > Ruscheweyh, H.-J., Milanese, A., Paoli, L., Karcher, N., Clayssen, Q., Keller, M. I., Wirbel, J., Bork, P., Mende, D. R., Zeller, G., & Sunagawa, S. (2022). Cultivation-independent genomes greatly expand taxonomic-profiling capabilities of mOTUs across various environments. Microbiome, 10(1), 212. doi: 10.1186/s40168-022-01410-z - [Krona](https://doi.org/10.1186/1471-2105-12-385) > Ondov, Brian D., Nicholas H. Bergman, and Adam M. Phillippy. 2011. Interactive metagenomic visualization in a Web browser. BMC Bioinformatics 12 (1): 385. doi: 10.1186/1471-2105-12-385. ## 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) - [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. ## Data - [Maixner (2021)](https://doi.org/10.1016/j.cub.2021.09.031) (CI Test Data) > Maixner, Frank, Mohamed S. Sarhan, Kun D. Huang, Adrian Tett, Alexander Schoenafinger, Stefania Zingale, Aitor Blanco-Míguez, et al. 2021. “Hallstatt Miners Consumed Blue Cheese and Beer during the Iron Age and Retained a Non-Westernized Gut Microbiome until the Baroque Period.” Current Biology: CB 31 (23): 5149–62.e6. doi: 10.1016/j.cub.2021.09.031. - [Meslier (2022)](https://doi.org/10.1038/s41597-022-01762-z) (AWS Full Test data) > Meslier, Victoria, Benoit Quinquis, Kévin Da Silva, Florian Plaza Oñate, Nicolas Pons, Hugo Roume, Mircea Podar, and Mathieu Almeida. 2022. “Benchmarking Second and Third-Generation Sequencing Platforms for Microbial Metagenomics.” Scientific Data 9 (1): 694. doi: 10.1038/s41597-022-01762-z.