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

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
DOI: 10.1099/mgen.0.000074 Publication Date: 2016-06-27T11:12:23Z
ABSTRACT
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.
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