CITATIONS.md

nf-core/taxprofiler: Citations

nf-core

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

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

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

• MultiQC

  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

  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

  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

  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

  • 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

  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

  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

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

• 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

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

• PRINSEQ++

  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

  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

  Li, H. (2018). Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics , 34(18), 3094–3100. https://doi.org/10.1093/bioinformatics/bty191

• SAMTools

  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

  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

  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

• MetaPhlAn

  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

  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

  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

  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

  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

  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

  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

  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

  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

• Krona

  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

  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

Software packaging/containerisation tools

• Anaconda

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

• Bioconda

  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

  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

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

• Singularity

  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) (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) (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