HAYSTAC: A Bayesian framework for robust and rapid species identification in high-throughput sequencing data.

ABSTRACT: Identification of specific species in metagenomic samples is critical for several key applications, yet many tools available require large computational power and are often prone to false positive identifications. Here we describe High-AccuracY and Scalable Taxonomic Assignment of MetagenomiC data (HAYSTAC), which can estimate the probability that a specific taxon is present in a metagenome. HAYSTAC provides a user-friendly tool to construct databases, based on publicly available genomes, that are used for competitive read mapping. It then uses a novel Bayesian framework to infer the abundance and statistical support for each species identification and provide per-read species classification. Unlike other methods, HAYSTAC is specifically designed to efficiently handle both ancient and mode

SUBMITTER: Dimopoulos EA 

PROVIDER: S-EPMC9555677 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature