If you use GraphBin-Tk in your work, please cite the relevant tools.

GraphBin

Vijini Mallawaarachchi, Anuradha Wickramarachchi, Yu Lin. GraphBin: Refined binning of metagenomic contigs using assembly graphs. Bioinformatics, Volume 36, Issue 11, June 2020, Pages 3307–3313, DOI: https://doi.org/10.1093/bioinformatics/btaa180

GraphBin2

Vijini G. Mallawaarachchi, Anuradha S. Wickramarachchi, and Yu Lin. GraphBin2: Refined and Overlapped Binning of Metagenomic Contigs Using Assembly Graphs. In 20th International Workshop on Algorithms in Bioinformatics (WABI 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 172, pp. 8:1-8:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020). DOI: https://doi.org/10.4230/LIPIcs.WABI.2020.8

Mallawaarachchi, V.G., Wickramarachchi, A.S. & Lin, Y. Improving metagenomic binning results with overlapped bins using assembly graphs. Algorithms Mol Biol 16, 3 (2021). DOI: https://doi.org/10.1186/s13015-021-00185-6

MetaCoAG

Mallawaarachchi, V., Lin, Y. (2022). MetaCoAG: Binning Metagenomic Contigs via Composition, Coverage and Assembly Graphs. In: Pe'er, I. (eds) Research in Computational Molecular Biology. RECOMB 2022. Lecture Notes in Computer Science(), vol 13278. Springer, Cham. DOI: https://doi.org/10.1007/978-3-031-04749-7_5

Vijini Mallawaarachchi and Yu Lin. Accurate Binning of Metagenomic Contigs Using Composition, Coverage, and Assembly Graphs. Journal of Computational Biology 2022 29:12, 1357-1376. DOI: https://doi.org/10.1089/cmb.2022.0262

Assemblers used to generate contigs and assembly graphs

Please cite the assembler used for metagenome assembly from the following list.

Sergey Nurk, Dmitry Meleshko, Anton Korobeynikov and Pavel A. Pevzner. metaSPAdes: a new versatile metagenomic assembler. Genome Research (2017) 27:5, 824-834. DOI: https://doi.org/10.1101/gr.213959.116

Dinghua Li, Chi-Man Liu, Ruibang Luo, Kunihiko Sadakane and Tak-Wah Lam. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 31:10 (2015), 1674-1676. DOI: https://doi.org/10.1093/bioinformatics/btv033

Mikhail Kolmogorov, Derek M. Bickhart, Bahar Behsaz, Alexey Gurevich, Mikhail Rayko, Sung Bong Shin, Kristen Kuhn, Jeffrey Yuan, Evgeny Polevikov, Timothy P. L. Smith and Pavel A. Pevzner. metaFlye: scalable long-read metagenome assembly using repeat graphs. Nature Methods 17, (2020), 1103–1110. DOI: https://doi.org/10.1038/s41592-020-00971-x

Other software

Mina Rho, Haixu Tang and Yuzhen Ye. FragGeneScan: predicting genes in short and error-prone reads. Nucleic Acids Research, Volume 38, Issue 20, 1 November 2010, Page e191. DOI: https://doi.org/10.1093/nar/gkq747

Eddy, S.R. (2011) Accelerated Profile HMM Searches. PLOS Computational Biology 7(10): e1002195. DOI: https://doi.org/10.1371/journal.pcbi.1002195

Making Sense from Sequence — cogent3. URL: https://cogent3.org/

Csardi, G., & Nepusz, T. (2006). The igraph software package for complex network research. InterJournal, Complex Systems, 1695. URL: https://python.igraph.org/

Aric A. Hagberg, Daniel A. Schult and Pieter J. Swart, “Exploring network structure, dynamics, and function using NetworkX”, in Proceedings of the 7th Python in Science Conference (SciPy2008), Gäel Varoquaux, Travis Vaught, and Jarrod Millman (Eds), (Pasadena, CA USA), pp. 11–15, Aug 2008. URL: https://networkx.org/

Harris, C.R., Millman, K.J., van der Walt, S.J. et al. Array programming with NumPy. Nature 585, 357–362 (2020). DOI: https://doi.org/10.1038/s41586-020-2649-2

Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, Stéfan J. van der Walt, Matthew Brett, Joshua Wilson, K. Jarrod Millman, Nikolay Mayorov, Andrew R. J. Nelson, Eric Jones, Robert Kern, Eric Larson, CJ Carey, İlhan Polat, Yu Feng, Eric W. Moore, Jake VanderPlas, Denis Laxalde, Josef Perktold, Robert Cimrman, Ian Henriksen, E.A. Quintero, Charles R Harris, Anne M. Archibald, Antônio H. Ribeiro, Fabian Pedregosa, Paul van Mulbregt, and SciPy 1.0 Contributors. (2020) SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python. Nature Methods, 17(3), 261-272. DOI: https://doi.org/10.1038/s41592-019-0686-2