# nf-core/mag: 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

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

  > Schubert, M., Lindgreen, S., and Orlando, L. 2016. "AdapterRemoval v2: Rapid Adapter Trimming, Identification, and Read Merging." BMC Research Notes 9 (February): 88. doi: 10.1186/s13104-016-1900-2

- [ALE](https://github.com/sc932/ALE)

  > Clark, S. C., Egan, R., Frazier, P. I., & Wang, Z. (2013). ALE: a generic assembly likelihood evaluation framework for assessing the accuracy of genome and metagenome assemblies. Bioinformatics, 29(4), 435-443. doi: 10.1093/bioinformatics/bts723

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

- [BCFtools](https://doi.org/10.1093/gigascience/giab008)

  > Danecek, Petr, et al. "Twelve years of SAMtools and BCFtools." Gigascience 10.2 (2021): giab008. doi: 10.1093/gigascience/giab008

- [Bowtie2](https://doi.org/10.1038/nmeth.1923)

  > Langmead, B. and Salzberg, S. L. 2012 Fast gapped-read alignment with Bowtie 2. Nature methods, 9(4), p. 357–359. doi: 10.1038/nmeth.1923.

- [BUSCO](https://doi.org/10.1007/978-1-4939-9173-0_14)

  > Seppey, M., Manni, M., & Zdobnov, E. M. (2019). BUSCO: assessing genome assembly and annotation completeness. In Gene prediction (pp. 227-245). Humana, New York, NY. doi: 10.1007/978-1-4939-9173-0_14.

- [CAT](https://doi.org/10.1186/s13059-019-1817-x)

  > von Meijenfeldt, F. B., Arkhipova, K., Cambuy, D. D., Coutinho, F. H., & Dutilh, B. E. (2019). Robust taxonomic classification of uncharted microbial sequences and bins with CAT and BAT. Genome biology, 20(1), 1-14. doi: 10.1186/s13059-019-1817-x.

- [CheckM](https://doi.org/10.1101/gr.186072.114)

  > Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P., & Tyson, G. W. (2015). CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Research, 25(7), 1043–1055. doi: 10.1101/gr.186072.114

- [CheckM2](https://doi.org/10.1038/s41592-023-01940-w)

  > Chklovski, A., Parks, D. H., Woodcroft, B. J., & Tyson, G. W. (2023). CheckM2: a rapid, scalable and accurate tool for assessing microbial genome quality using machine learning. Nature Methods, 20(8), 1203-1212. doi: 10.1038/s41592-023-01940-w

- [Chopper](https://doi.org/10.1093/bioinformatics/bty149)

  > De Coster W, D'Hert S, Schultz DT, Cruts M, Van Broeckhoven C. NanoPack: visualizing and processing long-read sequencing data. Bioinformatics. 2018 Aug 1;34(15):2666-2669. doi: 10.1093/bioinformatics/bty149

- [COMEBin](https://doi.org/10.1038/s41467-023-44290-z)

  > Wang Z, You R, Han H, Liu W, Sun F, Zhu S. Effective binning of metagenomic contigs using contrastive multi-view representation learning. Nat Commun. 2024 Jan 17;15(1):585. doi: 10.1038/s41467-023-44290-z. PMID: 38233391; PMCID: PMC10794208.

- [CONCOCT](https://doi.org/10.1038/nmeth.3103)

  > Alneberg, J., Bjarnason, B. S., de Bruijn, I., Schirmer, M., Quick, J., Ijaz, U. Z., Lahti, L., Loman, N. J., Andersson, A. F., & Quince, C. (2014). Binning metagenomic contigs by coverage and composition. Nature Methods, 11(11), 1144–1146. doi: 10.1038/nmeth.3103

- [MetaBinner](https://doi.org/10.1186/s13059-022-02832-6)

  > Wang Z, Huang P, You R, Sun F, Zhu S. MetaBinner: a high-performance and stand-alone ensemble binning method to recover individual genomes from complex microbial communities. Genome Biol. 2023 Jan 6;24(1):1. doi: 10.1186/s13059-022-02832-6. PMID: 36609515; PMCID: PMC9817263.

- [SemiBin2](https://doi.org/10.1038/s41467-022-29843-y)

  > Pan S, Zhu C, Zhao XM, Coelho LP. A deep siamese neural network improves metagenome-assembled genomes in microbiome datasets across different environments. Nat Commun. 2022 Apr 28;13(1):2326. doi: 10.1038/s41467-022-29843-y. PMID: 35484115; PMCID: PMC9051138.

- [DAS Tool](https://doi.org/10.1038/s41564-018-0171-1)

  > Sieber, C. M. K., et al. 2018. "Recovery of Genomes from Metagenomes via a Dereplication, Aggregation and Scoring Strategy." Nature Microbiology 3 (7): 836-43. doi: 10.1038/s41564-018-0171-1

- [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. doi: 10.1093/bioinformatics/bty560.

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

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

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

- [Flye](https://www.nature.com/articles/s41592-020-00971-x)

  > Kolmogorov, M., Bickhart, D.M., Behsaz, B. et al. metaFlye: scalable long-read metagenome assembly using repeat graphs. Nat Methods 17, 1103–1110 (2020). doi: 10.1038/s41592-020-00971-x

- [Freebayes](https://arxiv.org/abs/1207.3907)

  > Garrison E, Marth G. Haplotype-based variant detection from short-read sequencing. arXiv preprint arXiv:1207.3907 [q-bio.GN] 2012

- [geNomad](https://doi.org/10.1038/s41587-023-01953-y)

  > Camargo, A. P., et al. (2023). Identification of mobile genetic elements with geNomad. Nature Biotechnology 42, 1303–1312. doi: 10.1038/s41587-023-01953-y

- [GTDB-Tk](https://doi.org/10.1093/bioinformatics/btz848)

  > Chaumeil, P. A., Mussig, A. J., Hugenholtz, P., & Parks, D. H. (2020). GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics , 36(6), 1925–1927. doi: 10.1093/bioinformatics/btz848.

- [GUNC](https://doi.org/10.1186/s13059-021-02393-0.)

  > Orakov, A., Fullam, A., Coelho, A. P., Khedkar, S., Szklarczyk, D., Mende, D. R., Schmidt, T. S. B., and Bork, P.. 2021. “GUNC: Detection of Chimerism and Contamination in Prokaryotic Genomes.” Genome Biology 22 (1): 178. doi: 10.1186/s13059-021-02393-0.

- [BIgMAG](https://doi.org/10.12688/f1000research.152290.2)

  > Yepes-García, J., Falquet, L. (2024). Metagenome quality metrics and taxonomical annotation visualization through the integration of MAGFlow and BIgMAG. F1000Research 13:640. doi: 10.12688/f1000research.152290.2

- [MaxBin2](https://doi.org/10.1093/bioinformatics/btv638)

  > Yu-Wei, W., Simmons, B. A. & Singer, S. W. (2015) MaxBin 2.0: An Automated Binning Algorithm to Recover Genomes from Multiple Metagenomic Datasets. Bioinformatics 32 (4): 605–7. doi: 10.1093/bioinformatics/btv638.

- [MEGAHIT](https://doi.org/10.1016/j.ymeth.2016.02.020)

  > Li, D., Luo, R., Liu, C. M., Leung, C. M., Ting, H. F., Sadakane, K., ... & Lam, T. W. (2016). MEGAHIT v1. 0: a fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods, 102, 3-11. doi: 10.1016/j.ymeth.2016.02.020.

- [MetaBAT2](https://doi.org/10.7717/peerj.7359)

  > Kang, D. D., Li, F., Kirton, E., Thomas, A., Egan, R., An, H., & Wang, Z. (2019). MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ, 7, e7359. doi: 10.7717/peerj.7359.

- [MetaEuk](https://doi.org/10.1186/s40168-020-00808-x)

  > Levy Karin, E., Mirdita, M. & Söding, J. MetaEuk—sensitive, high-throughput gene discovery, and annotation for large-scale eukaryotic metagenomics. Microbiome 8, 48 (2020). doi: 10.1186/s40168-020-00808-x

- [metaMDBG](https://doi.org/10.1038/s41587-023-01983-6)

  > Benoit, G., Raguideau, S., James, R. et al. High-quality metagenome assembly from long accurate reads with metaMDBG. Nat Biotechnol 42, 1378–1383 (2024). doi: 10.1038/s41587-023-01983-6

- [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

- [MMseqs2](https://www.nature.com/articles/nbt.3988)

  > Steinegger, M., Söding, J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat Biotechnol 35, 1026–1028 (2017). doi: 10.1038/nbt.3988

- [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.

- [NanoLyse](https://doi.org/10.1093/bioinformatics/bty149)

  > De Coster, W., D’Hert, S., Schultz, D. T., Cruts, M., & Van Broeckhoven, C. (2018). NanoPack: visualizing and processing long-read sequencing data. Bioinformatics, 34(15), 2666-2669. doi: 10.1093/bioinformatics/bty149.

- [NanoPlot](https://doi.org/10.1093/bioinformatics/bty149)

  > De Coster, W., D’Hert, S., Schultz, D. T., Cruts, M., & Van Broeckhoven, C. (2018). NanoPack: visualizing and processing long-read sequencing data. Bioinformatics, 34(15), 2666-2669. doi: 10.1093/bioinformatics/bty149.

- [Nanoq](https://doi.org/10.21105/joss.02991)

  > Steinig, E., Coin, L. (2022). Nanoq: ultra-fast quality control for nanopore reads. Journal of Open Source Software, 7(69), 2991, doi: 10.21105/joss.02991

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

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

  > Bonenfant, Q., Noé, L., & Touzet, H. (2022). Porechop_ABI: discovering unknown adapters in ONT sequencing reads for downstream trimming. bioRxiv. 10.1101/2022.07.07.499093

- [Prodigal](https://pubmed.ncbi.nlm.nih.gov/20211023/)

  > Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010 Mar 8;11:119. doi: 10.1186/1471-2105-11-119. PMID: 20211023; PMCID: PMC2848648.

- [Prokka](https://pubmed.ncbi.nlm.nih.gov/24642063/)

  > Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014 Jul 15;30(14):2068-9. doi: 10.1093/bioinformatics/btu153. Epub 2014 Mar 18. PMID: 24642063.

- [PyDamage](https://doi.org/10.7717/peerj.11845)

  > Borry M, Hübner A, Rohrlach AB, Warinner C. 2021. PyDamage: automated ancient damage identification and estimation for contigs in ancient DNA de novo assembly. PeerJ 9:e11845 doi: 10.7717/peerj.11845

- [pypolca](https://doi.org/10.1099/mgen.0.001254)

  > Bouras, G., Judd, L. M., Edwards, R. A., Vreugde, S., Stinear, T. P., & Wick, R. R. (2024). How low can you go? Short-read polishing of Oxford Nanopore bacterial genome assemblies. Microbial Genomics, 10(6), 001254. doi: 10.1099/mgen.0.001254

- [SAMtools](https://doi.org/10.1093/bioinformatics/btp352)

  > Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., … 1000 Genome Project Data Processing Subgroup. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics , 25(16), 2078–2079. doi: 10.1093/bioinformatics/btp352.

- [Seqtk](https://github.com/lh3/seqtk)

- [SPAdes](https://doi.org/10.1101/gr.213959.116)

  > Nurk, S., Meleshko, D., Korobeynikov, A., & Pevzner, P. A. (2017). metaSPAdes: a new versatile metagenomic assembler. Genome research, 27(5), 824-834. doi: 10.1101/gr.213959.116.

- [Tiara](https://doi.org/10.1093/bioinformatics/btab672)

  > Karlicki, M., Antonowicz, S., Karnkowska, A., 2022. Tiara: deep learning-based classification system for eukaryotic sequences. Bioinformatics 38, 344–350. doi: 10.1093/bioinformatics/btab672

- [Trimmomatic](https://doi.org/10.1093/bioinformatics/btu170)

  > Bolger, A. M., Lohse, M., & Usadel, B. (2014). Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics, 30(15), 2114-2120. doi: 10.1093/bioinformatics/btu170

## Data

- [Full-size test data](https://doi.org/10.1038/s41587-019-0191-2)

  > Bertrand, D., Shaw, J., Kalathiyappan, M., Ng, A. H. Q., Kumar, M. S., Li, C., ... & Nagarajan, N. (2019). Hybrid metagenomic assembly enables high-resolution analysis of resistance determinants and mobile elements in human microbiomes. Nature biotechnology, 37(8), 937-944. doi: 10.1038/s41587-019-0191-2.

## 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.
