SnapperDB: a database solution for routine sequencing analysis of bacterial isolates | Zendy

Timothy J. Dallman | Zendy; Philip Ashton | Zendy; Ulf Schafer | Zendy; Aleksey Jironkin | Zendy; Anaïs Painset | Zendy; Sharif Shaaban | Zendy; Hassan Hartman | Zendy; Richard Myers | Zendy; Anthony Underwood | Zendy; Claire Jenkins | Zendy; Kathie Grant | Zendy

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SnapperDB: a database solution for routine sequencing analysis of bacterial isolates

Author(s) -

Timothy J. Dallman,

Philip Ashton,

Ulf Schafer,

Aleksey Jironkin,

Anaïs Painset,

Sharif Shaaban,

Hassan Hartman,

Richard Myers,

Anthony Underwood,

Claire Jenkins,

Kathie Grant

Publication year - 2018

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bty212

Subject(s) - computer science , database , computational biology , biology

Real-time surveillance of infectious disease using whole genome sequencing data poses challenges in both result generation and communication. SnapperDB represents a set of tools to store bacterial variant data and facilitate reproducible and scalable analysis of bacterial populations. We also introduce the 'SNP address' nomenclature to describe the relationship between isolates in a population to the single nucleotide resolution. We announce the release of SnapperDB v1.0 a program for scalable routine SNP analysis and storage of microbial populations.

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