SolidBin: improving metagenome binning with semi-supervised normalized cut.

ABSTRACT:

Motivation

Metagenomic contig binning is an important computational problem in metagenomic research, which aims to cluster contigs from the same genome into the same group. Unlike classical clustering problem, contig binning can utilize known relationships among some of the contigs or the taxonomic identity of some contigs. However, the current state-of-the-art contig binning methods do not make full use of the additional biological information except the coverage and sequence composition of the contigs.

Results

We developed a novel contig binning method, Semi-supervised Spectral Normalized Cut for Binning (SolidBin), based on semi-supervised spectral clustering. Using sequence feature similarity and/or additional biological information, such as the reliable taxonomy assignm

SUBMITTER: Wang Z 

PROVIDER: S-EPMC6821242 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature