NASP: an accurate, rapid method for the identification of SNPs in WGS datasets that supports flexible input and output formats

• DOI: 10.1099/mgen.0.000074
• Publication Date: 2016-06-27T11:12:23Z
• Authors: Jason W. Sahl; Darrin Lemmer; Jason Travis; James M. Schupp; John D. Gillece; Maliha Aziz; Elizabeth M. Driebe; Kevin P. Drees; Nathan D. Hicks; Charles Hall Davi...; Crystal M. Hepp; David Earl Smith; Chandler Roe; David M. Engelthaler; David M. Wagner; Paul Keim
• Keywords: Molecular Epidemiology; 0303 health sciences; 03 medical and health sciences; Whole Genome Sequencing; Computer Simulation; Genomics; Sequence Analysis, DNA; Polymorphism, Single Nucleotide; Genome, Bacterial; Phylogeny; Software

Whole-genome sequencing (WGS) of bacterial isolates has become standard practice in many laboratories. Applications for WGS analysis include phylogeography and molecular epidemiology, using single nucleotide polymorphisms (SNPs) as the unit of evolution. NASP was developed as a reproducible method that scales well with the hundreds to thousands of WGS data typically used in comparative genomics applications. In this study, we demonstrate how NASP compares with other tools in the analysis of two real bacterial genomics datasets and one simulated dataset. Our results demonstrate that NASP produces similar, and often better, results in comparison with other pipelines, but is much more flexible in terms of data input types, job management systems, diversity of supported tools and output formats. We also demonstrate differences in results based on the choice of the reference genome and choice of inferring phylogenies from concatenated SNPs or alignments including monomorphic positions. NASP represents a source-available, version-controlled, unit-tested method and can be obtained from tgennorth.github.io/NASP.