Comprehensive benchmarking and ensemble approaches for metagenomic classifiers.

ABSTRACT:

Background

One of the main challenges in metagenomics is the identification of microorganisms in clinical and environmental samples. While an extensive and heterogeneous set of computational tools is available to classify microorganisms using whole-genome shotgun sequencing data, comprehensive comparisons of these methods are limited.

Results

In this study, we use the largest-to-date set of laboratory-generated and simulated controls across 846 species to evaluate the performance of 11 metagenomic classifiers. Tools were characterized on the basis of their ability to identify taxa at the genus, species, and strain levels, quantify relative abundances of taxa, and classify individual reads to the species level. Strikingly, the number of species identified by the 11 tools can

SUBMITTER: McIntyre ABR 

PROVIDER: S-EPMC5609029 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature