title: Nonpareil: a redundancy-based approach to assess the level of coverage in metagenomic datasets.
abstract: BACKGROUND
  Determining the fraction of the diversity within a microbial community sampled and the amount of sequencing required to cover the total diversity represent challenging issues for metagenomics studies. Owing to these limitations, central ecological questions with respect to the global distribution of microbes and the functional diversity of their communities cannot be robustly assessed.
  
  
  RESULTS
  We introduce Nonpareil, a method to estimate and project coverage in metagenomes. Nonpareil does not rely on high-quality assemblies, operational taxonomic unit calling or comprehensive reference databases; thus, it is broadly applicable to metagenomic studies. Application of Nonpareil on available metagenomic datasets provided estimates on the relative complexity of soil, freshwater and human microbiome communities, and suggested that ∼200 Gb of sequencing data are required for 95% abundance-weighted average coverage of the soil communities analyzed.
  
  
  METHODS
  Nonpareil is available at https://github.com/lmrodriguezr/nonpareil/ under the Artistic License 2.0.
authors.affiliation: Center for Bioinformatics and Computational Genomics, School of Biology and School of Civil and Environmental Engineering, Georgia Institute of Technology, 311 Ferst Drive, Ford ES&T Building, Suite 3224, Atlanta, GA 30332, USA.
authors.forename: Luis M
authors.initials: LM
authors.lastname: Rodriguez-R
authors.forename: Konstantinos T
authors.initials: KT
authors.lastname: Konstantinidis
mesh_terms: D000465:Algorithms; D054892:Metagenome; D056186:Metagenomics / Q000379:methods*; D064307:Microbiota; D012988:Soil Microbiology