# nf-core/taxprofiler: Citations

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

> Ewels, P. A., Peltzer, A., Fillinger, S., Patel, H., Alneberg, J., Wilm, A., Garcia, M. U., Di Tommaso, P., & Nahnsen, S. (2020). The nf-core framework for community-curated bioinformatics pipelines. In Nature Biotechnology (Vol. 38, Issue 3). https://doi.org/10.1038/s41587-020-0439-x

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

> Di Tommaso, P., Chatzou, M., Floden, E. W., Barja, P. P., Palumbo, E., & Notredame, C. (2017). Nextflow enables reproducible computational workflows. In Nature Biotechnology (Vol. 35, Issue 4). https://doi.org/10.1038/nbt.3820

## Pipeline tools

- [FastQC](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/)

  > Andrews, S. (2010). FastQC: A Quality Control Tool for High Throughput Sequence Data [Online].

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

  > Ewels, P., Magnusson, M., Lundin, S., & Käller, M. (2016). MultiQC: Summarize analysis results for multiple tools and samples in a single report. Bioinformatics, 32(19). https://doi.org/10.1093/bioinformatics/btw354

- [falco](https://doi.org/10.12688/f1000research.21142.2)

  > de Sena Brandine, G., & Smith, A. D. (2021). Falco: high-speed FastQC emulation for quality control of sequencing data. F1000Research, 8(1874), 1874. https://doi.org/10.12688/f1000research.21142.2

- [fastp](https://doi.org/10.1093/bioinformatics/bty560)

  > Chen, S., Zhou, Y., Chen, Y., & Gu, J. (2018). fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics , 34(17), i884–i890. https://doi.org/10.1093/bioinformatics/bty560

- [AdapterRemoval2](https://doi.org/10.1186/s13104-016-1900-2)

  > Schubert, M., Lindgreen, S., & Orlando, L. (2016). AdapterRemoval v2: rapid adapter trimming, identification, and read merging. BMC Research Notes, 9, 88. https://doi.org/10.1186/s13104-016-1900-2

- [Nonpareil](https://doi.org/10.1128/mSystems.00039-18)
  - Rodriguez-R, L. M., Gunturu, S., Tiedje, J. M., Cole, J. R., & Konstantinidis, K. T. (2018). Nonpareil 3: Fast Estimation of Metagenomic Coverage and Sequence Diversity. mSystems, 3(3). https://doi.org/10.1128/mSystems.00039-18

- [Porechop](https://github.com/rrwick/Porechop)

  > Wick, R. R., Judd, L. M., Gorrie, C. L., & Holt, K. E. (2017). Completing bacterial genome assemblies with multiplex MinION sequencing. Microbial Genomics, 3(10), e000132. https://doi.org/10.1099/mgen.0.000132

- [Porechop_ABI](https://github.com/bonsai-team/Porechop_ABI)

  > Bonenfant, Q., Noé, L., & Touzet, H. (2023). Porechop_ABI: discovering unknown adapters in Oxford Nanopore Technology sequencing reads for downstream trimming. Bioinformatics Advances, 3(1):vbac085. https://10.1093/bioadv/vbac085

- [Filtlong](https://github.com/rrwick/Filtlong)

  > Wick R (2021) Filtlong, URL: https://github.com/rrwick/Filtlong

- [nanoq](https://github.com/esteinig/nanoq)

  > Steinig, E., & Coin, L. (2022). Nanoq: ultra-fast quality control for nanopore reads. Journal of Open Source Software, 7(69). https://doi.org/10.21105/joss.02991

- [BBTools](http://sourceforge.net/projects/bbmap/)

  > Bushnell B. (2022) BBMap, URL: http://sourceforge.net/projects/bbmap/

- [PRINSEQ++](https://doi.org/10.7287/peerj.preprints.27553v1)

  > Cantu, V. A., Sadural, J., & Edwards, R. (2019). PRINSEQ++, a multi-threaded tool for fast and efficient quality control and preprocessing of sequencing datasets (e27553v1). PeerJ Preprints. https://doi.org/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. https://doi.org/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. https://doi.org/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). https://doi.org/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), e104. https://doi.org/10.7717/peerj-cs.104

- [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

- [MetaPhlAn](https://doi.org/10.1038/s41587-023-01688-w)

  > Blanco-Míguez, A., Beghini, F., Cumbo, F., McIver, L. J., Thompson, K. N., Zolfo, M., Manghi, P., Dubois, L., Huang, K. D., Thomas, A. M., Nickols, W. A., Piccinno, G., Piperni, E., Punčochář, M., Valles-Colomer, M., Tett, A., Giordano, F., Davies, R., Wolf, J., … Segata, N. (2023). Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4. Nature Biotechnology, 1–12. https://doi.org/10.1038/s41587-023-01688-w

- [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

- [MEGAN](https://doi.org/10.1371/journal.pcbi.1004957)

  > Huson, D. H., Beier, S., Flade, I., Górska, A., El-Hadidi, M., Mitra, S., Ruscheweyh, H.-J., & Tappu, R. (2016). MEGAN Community Edition - Interactive Exploration and Analysis of Large-Scale Microbiome Sequencing Data. PLoS Computational Biology, 12(6), e1004957. https://doi.org/10.1371/journal.pcbi.1004957

- [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

- [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

- [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

- [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. https://doi.org/10.1186/s40168-022-01410-z

- [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

- [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

- [melon](https://doi.org/10.1186/s13059-024-03363-y)

  > Chen, X., Yin, X., Shi, X., Yan, W., Yang, Y., Liu, L., & Zhang, T. (2024). Melon: metagenomic long-read-based taxonomic identification and quantification using marker genes. Genome Biology, 25(1), 226. https://doi.org/10.1186/s13059-024-03363-y

- [Krona](https://doi.org/10.1186/1471-2105-12-385)

  > Ondov, B. D., Bergman, N. H., & Phillippy, A. M. (2011). Interactive metagenomic visualization in a Web browser. BMC Bioinformatics, 12. https://doi.org/10.1186/1471-2105-12-385

- [TAXPASTA](https://doi.org/10.21105/joss.05627)

  > Beber, M. E., Borry, M., Stamouli, S., & Fellows Yates, J. A. (2023). TAXPASTA: TAXonomic Profile Aggregation and STAndardisation. Journal of Open Source Software, 8(87), 5627. https://doi.org/10.21105/joss.05627

- [sylph](https://doi.org/10.1038/s41587-024-02412-y)

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

- [MetaCache](https://doi.org/10.1093/bioinformatics/btx520)

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

## 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/)

  > Dale, R., Grüning, B., Sjödin, A., Rowe, J., Chapman, B. A., Tomkins-Tinch, C. H., Valieris, R., Batut, B., Caprez, A., Cokelaer, T., Yusuf, D., Beauchamp, K. A., Brinda, K., Wollmann, T., Corguillé, G. Le, Ryan, D., Bretaudeau, A., Hoogstrate, Y., Pedersen, B. S., … Köster, J. (2018). Bioconda: Sustainable and comprehensive software distribution for the life sciences. Nature Methods, 15(7). https://doi.org/10.1038/s41592-018-0046-7

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

  > Da Veiga Leprevost, F., Grüning, B. A., Alves Aflitos, S., Röst, H. L., Uszkoreit, J., Barsnes, H., Vaudel, M., Moreno, P., Gatto, L., Weber, J., Bai, M., Jimenez, R. C., Sachsenberg, T., Pfeuffer, J., Vera Alvarez, R., Griss, J., Nesvizhskii, A. I., & Perez-Riverol, Y. (2017). BioContainers: An open-source and community-driven framework for software standardization. Bioinformatics, 33(16). https://doi.org/10.1093/bioinformatics/btx192

- [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, G. M., Sochat, V., & Bauer, M. W. (2017). Singularity: Scientific containers for mobility of compute. PLoS ONE, 12(5). https://doi.org/10.1371/journal.pone.0177459

## Data

- [Maixner (2021)](https://doi.org/10.1016/j.cub.2021.09.031) (CI Test Data)

  > Maixner, F., Sarhan, M. S., Huang, K. D., Tett, A., Schoenafinger, A., Zingale, S., Blanco-Míguez, A., Manghi, P., Cemper-Kiesslich, J., Rosendahl, W., Kusebauch, U., Morrone, S. R., Hoopmann, M. R., Rota-Stabelli, O., Rattei, T., Moritz, R. L., Oeggl, K., Segata, N., Zink, A., … Kowarik, K. (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, 31(23). https://doi.org/10.1016/j.cub.2021.09.031

- [Meslier (2022)](https://doi.org/10.1038/s41597-022-01762-z) (AWS Full Test data)

  > Meslier, V., Quinquis, B., Da Silva, K., Plaza Oñate, F., Pons, N., Roume, H., Podar, M., & Almeida, M. (2022). Benchmarking second and third-generation sequencing platforms for microbial metagenomics. Scientific Data, 9(1). https://doi.org/10.1038/s41597-022-01762-z
