Binning metagenomic contigs by coverage and composition

By J. Alneberg, Brynjar Smári Bjarnason, I. de Bruijn, M. Schirmer, Joshua Quick, Umer Zeeshan Ijaz, L. Lahti, Nicholas J. Loman, Anders F. Andersson, Christopher Quince. Nature Methods, 2014

2,352 citations recorded by the source corpus.

Subfields: Food Science, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/1f28f53a6f6fcba883def8f8227864602ab56000

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Citations in the corpus

A review of methods and databases for metagenomic classification and assembly (2019, methodology): “COCACOLA [113] works similarly to CONCOCT but using different distance metrics and different clustering rules.”
Current challenges and best-practice protocols for microbiome analysis (2019, methodology): “On the contrary, CONCOCT uses Gaussian mixture models for clustering contigs by combining both tetranucleotide frequencies and differential abundances covering multiple samples for binning [105].”
Tracking microbial colonization in fecal microbiota transplantation experiments via genome-resolved metagenomics (2017, methodology): “We then interactively refined each CONCOCT bin that exhibit “conflation error” (where one bin describes multiple populations) using the program “anvi-refine” based on tetra-nucleotide frequency, taxonomy, mean coverage, and completion and redundancy estimates based on bacterial and archaeal single-c”
Robust taxonomic classification of uncharted microbial sequences and bins with CAT and BAT (2019, neutral): “, [28, 29]), CAT classification can be considered as”
Critical Assessment of Metagenome Interpretation: the second round of challenges (2021, background): “Overall, mOTUs v.2.5.1 and MetaPhlAn v.2.9.22 ranked best across taxonomic ranks and metrics on the marine and plant-associated datasets, and mOTUs v.cami1 and MetaPhlAn v.2.9.22 on the strain-madness dataset (Table 1, Supplementary Tables 33, 35 and 37 and Supplementary Fig.”
BlobTools: Interrogation of genome assemblies (2017, methodology): “Anvi'o can employ CONCOCT to automatically partition contigs into genome bins, however, it is only optional.”
Microbial strain-level population structure and genetic diversity from metagenomes (2017, neutral): “…phylogenies as evaluated on a number of semisynthetic and real spike-in samples, although assembly or pangenome-based meth-ods (Sharon et al. 2013; Alneberg et al. 2014; Raveh-Sadka et al. 2015; Scholz et al. 2016) are still required to identify strain-specific gene repertoires.”
Evaluating the Information Content of Shallow Shotgun Metagenomics (2018, background): “These concerns can be alleviated to some extent using deep shotgun sequencing and metagenomic assembly (10), coabundance clustering (11), or proximity-based assembly (28), and de novo identification of strains from complex metagenomes remains an active area of research.”
DNA Sequencing as a Tool to Monitor Marine Ecological Status (2017, background): “A growing number of assemblers (Boisvert et al., 2012; Peng et al., 2012) and binning tools (Alneberg et al., 2014; Imelfort et al., 2014; Nurk et al., 2017) are available that assemble short sequencing reads into larger contigs and subsequently combine them into bins based on, for example,…”
MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities (2015, methodology): “0 (Alneberg et al., 2014), GroopM v.”