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

Timothy Dallman; Philip Ashton; Ulf Schafer; Aleksey Jironkin; Anais Painset; Sharif Shaaban; Hassan Hartman; Richard Myers; Anthony Underwood; Claire Jenkins; Kathie Grant

doi:10.1093/bioinformatics/bty212

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

Timothy Dallman^*, Philip Ashton, Ulf Schafer, Aleksey Jironkin, Anais Painset, Sharif Shaaban, Hassan Hartman, Richard Myers, Anthony Underwood, Claire Jenkins, Kathie Grant

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

Summary: 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.

Availability and implementation: SnapperDB is implemented as a python application under the open source BSD license. All code and user guides are available at https://github.com/phe-bioinformatics/snapperdb. Reference genomes and SnapperDB configs are available at https://github.com/phe-bioinformatics/snapperdb_references.

Original language	English
Pages (from-to)	3028-3029
Number of pages	2
Journal	Bioinformatics
Volume	34
Issue number	17
DOIs	https://doi.org/10.1093/bioinformatics/bty212
Publication status	Published - 1 Sept 2018
Externally published	Yes

Keywords

Databases, Factual
Genome
Sequence Analysis
Software
Whole Genome Sequencing

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10.1093/bioinformatics/bty212

Cite this

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title = "SnapperDB: a database solution for routine sequencing analysis of bacterial isolates",

abstract = "Summary: 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.Availability and implementation: SnapperDB is implemented as a python application under the open source BSD license. All code and user guides are available at https://github.com/phe-bioinformatics/snapperdb. Reference genomes and SnapperDB configs are available at https://github.com/phe-bioinformatics/snapperdb_references.",

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year = "2018",

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doi = "10.1093/bioinformatics/bty212",

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T2 - a database solution for routine sequencing analysis of bacterial isolates

AU - Dallman, Timothy

AU - Ashton, Philip

AU - Schafer, Ulf

AU - Jironkin, Aleksey

AU - Painset, Anais

AU - Shaaban, Sharif

AU - Hartman, Hassan

AU - Myers, Richard

AU - Underwood, Anthony

AU - Jenkins, Claire

AU - Grant, Kathie

PY - 2018/9/1

Y1 - 2018/9/1

N2 - Summary: 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.Availability and implementation: SnapperDB is implemented as a python application under the open source BSD license. All code and user guides are available at https://github.com/phe-bioinformatics/snapperdb. Reference genomes and SnapperDB configs are available at https://github.com/phe-bioinformatics/snapperdb_references.

AB - Summary: 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.Availability and implementation: SnapperDB is implemented as a python application under the open source BSD license. All code and user guides are available at https://github.com/phe-bioinformatics/snapperdb. Reference genomes and SnapperDB configs are available at https://github.com/phe-bioinformatics/snapperdb_references.

KW - Databases, Factual

KW - Genome

KW - Sequence Analysis

KW - Software

KW - Whole Genome Sequencing

U2 - 10.1093/bioinformatics/bty212

DO - 10.1093/bioinformatics/bty212

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EP - 3029

JO - Bioinformatics

JF - Bioinformatics

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ER -

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

Abstract

Keywords

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