Improving contig binning of metagenomic data using [Formula: see text] oligonucleotide frequency dissimilarity.

ABSTRACT:

Background

Metagenomics sequencing provides deep insights into microbial communities. To investigate their taxonomic structure, binning assembled contigs into discrete clusters is critical. Many binning algorithms have been developed, but their performance is not always satisfactory, especially for complex microbial communities, calling for further development.

Results

According to previous studies, relative sequence compositions are similar across different regions of the same genome, but they differ between distinct genomes. Generally, current tools have used the normalized frequency of k-tuples directly, but this represents an absolute, not relative, sequence composition. Therefore, we attempted to model contigs using relative k-tuple composition, followed by measuring di

SUBMITTER: Wang Y 

PROVIDER: S-EPMC5607646 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature