title: Accurate binning of metagenomic contigs via automated clustering sequences using information of genomic signatures and marker genes.
abstract: Metagenomics, the application of shotgun sequencing, facilitates the reconstruction of the genomes of individual species from natural environments. A major challenge in the genome recovery domain is to agglomerate or 'bin' sequences assembled from metagenomic reads into individual groups. Metagenomic binning without consideration of reference sequences enables the comprehensive discovery of new microbial organisms and aids in the microbial genome reconstruction process. Here we present MyCC, an automated binning tool that combines genomic signatures, marker genes and optional contig coverages within one or multiple samples, in order to visualize the metagenomes and to identify the reconstructed genomic fragments. We demonstrate the superior performance of MyCC compared to other binning tools including CONCOCT, GroopM, MaxBin and MetaBAT on both synthetic and real human gut communities with a small sample size (one to 11 samples), as well as on a large metagenome dataset (over 250 samples). Moreover, we demonstrate the visualization of metagenomes in MyCC to aid in the reconstruction of genomes from distinct bins. MyCC is freely available at http://sourceforge.net/projects/sb2nhri/files/MyCC/.
authors.affiliation: Institute of Population Health Sciences, National Health Research Institutes, Miaoli County 35053, Taiwan.
authors.forename: Hsin-Hung
authors.initials: HH
authors.lastname: Lin
authors.affiliation: Institute of Population Health Sciences, National Health Research Institutes, Miaoli County 35053, Taiwan.
authors.forename: Yu-Chieh
authors.initials: YC
authors.lastname: Liao
mesh_terms: D000465:Algorithms; D001331:Automation / Q000379:methods*; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D020451:Contig Mapping; D000069196:Gastrointestinal Microbiome; D005796:Genes; D006801:Humans; D054892:Metagenome; D056186:Metagenomics / Q000379:methods*; D064307:Microbiota