title: MetaCluster 5.0: a two-round binning approach for metagenomic data for low-abundance species in a noisy sample.
abstract: BACKGROUND
  Metagenomic binning remains an important topic in metagenomic analysis. Existing unsupervised binning methods for next-generation sequencing (NGS) reads do not perform well on (i) samples with low-abundance species or (ii) samples (even with high abundance) when there are many extremely low-abundance species. These two problems are common for real metagenomic datasets. Binning methods that can solve these problems are desirable.
  
  
  RESULTS
  We proposed a two-round binning method (MetaCluster 5.0) that aims at identifying both low-abundance and high-abundance species in the presence of a large amount of noise due to many extremely low-abundance species. In summary, MetaCluster 5.0 uses a filtering strategy to remove noise from the extremely low-abundance species. It separate reads of high-abundance species from those of low-abundance species in two different rounds. To overcome the issue of low coverage for low-abundance species, multiple w values are used to group reads with overlapping w-mers, whereas reads from high-abundance species are grouped with high confidence based on a large w and then binning expands to low-abundance species using a relaxed (shorter) w. Compared to the recent tools, TOSS and MetaCluster 4.0, MetaCluster 5.0 can find more species (especially those with low abundance of say 6× to 10×) and can achieve better sensitivity and specificity using less memory and running time.
  
  
  BACKGROUND
  http://i.cs.hku.hk/~alse/MetaCluster/
  
  
  BACKGROUND
  chin@cs.hku.hk.
authors.affiliation: Department of Computer Science, The University of Hong Kong, Hong Kong.
authors.forename: Yi
authors.initials: Y
authors.lastname: Wang
authors.forename: Henry C M
authors.initials: HC
authors.lastname: Leung
authors.forename: S M
authors.initials: SM
authors.lastname: Yiu
authors.forename: Francis Y L
authors.initials: FY
authors.lastname: Chin
mesh_terms: D000465:Algorithms; D056186:Metagenomics / Q000379:methods*; D012680:Sensitivity and Specificity; D017422:Sequence Analysis, DNA / Q000379:methods; D012984:Software