TaxMaps: comprehensive and highly accurate taxonomic classification of short-read data in reasonable time.

Abstract

High-throughput sequencing is a revolutionary technology for the analysis of metagenomic samples. However, querying large volumes of reads against comprehensive DNA/RNA databases in a sensitive manner can be compute-intensive. Here, we present taxMaps, a highly efficient, sensitive, and fully scalable taxonomic classification tool. Using a combination of simulated and real metagenomics data sets, we demonstrate that taxMaps is more sensitive and more precise than widely used taxonomic classifiers and is capable of delivering classification accuracy comparable to that of BLASTN, but at up to three orders of magnitude less computational cost.