rhysnewell · rhysnewell · Aug 11, 2023 · Aug 9, 2023 · Aug 9, 2023 · Aug 9, 2023
diff --git a/docs/citations.md b/docs/citations.md
@@ -1,42 +1,44 @@
----
-title: Citations
----
-
-Citations
-========
-
-If you use aviary then please be aware that you are using a great number of other programs and aviary wrapping around them.
-You should cite all of these tools as well, or whichever tools you know that you are using. To make this easy for you
-we have provided the following list of citations for you to use in alphabetical order. This list will be updated as new
-modules are added to aviary.
-
-## QC
-- De Coster, W., D’Hert, S., Schultz, D. T., Cruts, M. & Van Broeckhoven, C. NanoPack: visualizing and processing long-read sequencing data. Bioinformatics 34, 2666–2669 (2018).
-
-## Assembly
-- Kolmogorov, M., Yuan, J., Lin, Y. & Pevzner, P. A. Assembly of long, error-prone reads using repeat graphs. Nature Biotechnology 37, 540–546 (2019).
-- Hunt, M. et al. Circlator: automated circularization of genome assemblies using long sequencing reads. Genome Biology 16, 294 (2015).
-- Vaser, R., Sović, I., Nagarajan, N. & Šikić, M. Fast and accurate de novo genome assembly from long uncorrected reads. Genome Res 27, 737–746 (2017).
-- Walker, B. J. et al. Pilon: An Integrated Tool for Comprehensive Microbial Variant Detection and Genome Assembly Improvement. PLOS ONE 9, e112963 (2014).
-- Bankevich, A. et al. SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing. J Comput Biol 19, 455–477 (2012).
-- Wick, R. R., Judd, L. M., Gorrie, C. L. & Holt, K. E. Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads. PLOS Computational Biology 13, e1005595 (2017).
-- Li, D., Liu, C.-M., Luo, R., Sadakane, K. & Lam, T.-W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 31, 1674–1676 (2015).
-
-## Read mapping
-- Li, H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34, 3094–3100 (2018).
-- Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
-
-## Binning
-- Alneberg, J. et al. Binning metagenomic contigs by coverage and composition. Nat Methods 11, 1144–1146 (2014).
-- Nissen, J. N. et al. Improved metagenome binning and assembly using deep variational autoencoders. Nature Biotechnology 1–6 (2021) doi:10.1038/s41587-020-00777-4.
-- Kang, D. D., Froula, J., Egan, R. & Wang, Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ 3, e1165 (2015).
-- Kang, D. D. et al. MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ 7, (2019).
-- Sieber, C. M. K. et al. Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy. Nature Microbiology 3, 836–843 (2018).
-- Pan, S., Zhu, C., Zhao, X.-M. & Coelho, L. P. A deep siamese neural network improves metagenome-assembled genomes in microbiome datasets across different environments. Nat Commun 13, 2326 (2022).
-- Wu, Y.-W., Simmons, B. A. & Singer, S. W. MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets. Bioinformatics 32, 605–607 (2016).
-
-## Annotation
-- Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P. & Tyson, G. W. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 25, 1043–1055 (2015).
-- Huerta-Cepas, J. et al. eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Research 47, D309–D314 (2019).
-- Chaumeil, P.-A., Mussig, A. J., Hugenholtz, P. & Parks, D. H. GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics 36, 1925–1927 (2020).
-- Boyd, J. A., Woodcroft, B. J. & Tyson, G. W. GraftM: a tool for scalable, phylogenetically informed classification of genes within metagenomes. Nucleic Acids Research 46, e59 (2018).
+---
+title: Citations
+---
+
+Citations
+========
+
+If you use aviary then please be aware that you are using a great number of other programs and aviary wrapping around them.
+You should cite all of these tools as well, or whichever tools you know that you are using. To make this easy for you
+we have provided the following list of citations for you to use in alphabetical order. This list will be updated as new
+modules are added to aviary.
+
+## QC
+- **NanoPack**: De Coster, W., D’Hert, S., Schultz, D. T., Cruts, M. & Van Broeckhoven, C. NanoPack: visualizing and processing long-read sequencing data. Bioinformatics 34, 2666–2669 (2018). https://doi.org/10.1093/bioinformatics/bty149
+
+## Assembly
+- **Flye**: Kolmogorov, M., Yuan, J., Lin, Y. & Pevzner, P. A. Assembly of long, error-prone reads using repeat graphs. Nature Biotechnology 37, 540–546 (2019). https://doi.org/10.1038/s41587-019-0072-8
+- **Circulator**: Hunt, M. et al. Circlator: automated circularization of genome assemblies using long sequencing reads. Genome Biology 16, 294 (2015). https://doi.org/10.1186/s13059-015-0849-0
+- **Racon**: Vaser, R., Sović, I., Nagarajan, N. & Šikić, M. Fast and accurate de novo genome assembly from long uncorrected reads. Genome Res 27, 737–746 (2017). https://doi.org/10.1101/gr.214270.116 
+- **Pilon**: Walker, B. J. et al. Pilon: An Integrated Tool for Comprehensive Microbial Variant Detection and Genome Assembly Improvement. PLOS ONE 9, e112963 (2014). https://doi.org/10.1371/journal.pone.0112963
+- **metaSPAdes**: Nurk, S., Meleshko, D., Korobeynikov, A., & Pevzner, P. A. (2017). metaSPAdes: a new versatile metagenomic assembler. Genome research, 27(5), 824-834. https://doi.org/10.1101/gr.213959.116
+- **Unicycler**: Wick, R. R., Judd, L. M., Gorrie, C. L. & Holt, K. E. Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads. PLOS Computational Biology 13, e1005595 (2017). https://doi.org/10.1371/journal.pcbi.1005595
+- **MEGAHIT**: Li, D., Liu, C.-M., Luo, R., Sadakane, K. & Lam, T.-W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 31, 1674–1676 (2015). https://doi.org/10.1093/bioinformatics/btv033
+
+## Read mapping
+- **Minimap2**: Li, H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34, 3094–3100 (2018). https://doi.org/10.1093/bioinformatics/bty191
+- **samtools**: Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009). https://doi.org/10.1093/bioinformatics/btp352
+
+## Binning
+- **CONCOCT**: Alneberg, J. et al. Binning metagenomic contigs by coverage and composition. Nat Methods 11, 1144–1146 (2014). https://doi.org/10.1038/nmeth.3103
+- **VAMB**: Nissen, J. N. et al. Improved metagenome binning and assembly using deep variational autoencoders. Nature Biotechnology 1–6 (2021) doi:10.1038/s41587-020-00777-4. https://doi.org/10.1038/s41587-020-00777-4
+- **MetaBAT**: Kang, D. D., Froula, J., Egan, R. & Wang, Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ 3, e1165 (2015). https://doi.org/10.7717/peerj.1165
+- **MetaBAT2**: Kang, D. D. et al. MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ 7, (2019). https://doi.org/10.7717/peerj.7359
+- **DAS Tool**: Sieber, C. M. K. et al. Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy. Nature Microbiology 3, 836–843 (2018).
+https://doi.org/10.1038/s41564-018-0171-1
+- **SemiBin2**: Pan, S., Zhao, X. M., & Coelho, L. P. (2023). SemiBin2: self-supervised contrastive learning leads to better MAGs for short-and long-read sequencing, Bioinformatics, Volume 39, Issue Supplement_1, June 2023, Pages i21–i29. https://doi.org/10.1093/bioinformatics/btad209
+- **MaxBin 2.0**: Wu, Y.-W., Simmons, B. A. & Singer, S. W. MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets. Bioinformatics 32, 605–607 (2016). https://doi.org/10.1093/bioinformatics/btv638
+
+## Annotation
+- **CheckM2**: 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, 1-10. https://doi.org/10.1038/s41592-023-01940-w
+- **CheckM**: Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P. & Tyson, G. W. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 25, 1043–1055 (2015). https://doi.org/10.1101/gr.186072.114 
+- **eggNOG mapper 2**: Cantalapiedra, C. P., Hernández-Plaza, A., Letunic, I., Bork, P., & Huerta-Cepas, J. (2021). eggNOG-mapper v2: functional annotation, orthology assignments, and domain prediction at the metagenomic scale. Molecular biology and evolution, 38(12), 5825-5829. https://doi.org/10.1093/molbev/msab293
+- **GTDB-Tk 2**: Chaumeil, P. A., Mussig, A. J., Hugenholtz, P., & Parks, D. H. (2022). GTDB-Tk v2: memory friendly classification with the genome taxonomy database. Bioinformatics, 38(23), 5315-5316. https://doi.org/10.1093/bioinformatics/btac672
+- **GraftM**: Boyd, J. A., Woodcroft, B. J. & Tyson, G. W. GraftM: a tool for scalable, phylogenetically informed classification of genes within metagenomes. Nucleic Acids Research 46, e59 (2018). https://doi.org/10.1093/nar/gky174