LocusTrack: integrated visualization of GWAS results and genomic annotation

Cuellar-Partida, Gabriel, Renteria, Miguel E. and MacGregor, Stuart (2015) LocusTrack: integrated visualization of GWAS results and genomic annotation. Source Code for Biology and Medicine, 10 1: 1.1-1.4. doi:10.1186/s13029-015-0032-8

Author Cuellar-Partida, Gabriel
Renteria, Miguel E.
MacGregor, Stuart
Title LocusTrack: integrated visualization of GWAS results and genomic annotation
Journal name Source Code for Biology and Medicine   Check publisher's open access policy
ISSN 1751-0473
Publication date 2015-02-03
Year available 2015
Sub-type Article (original research)
DOI 10.1186/s13029-015-0032-8
Open Access Status DOI
Volume 10
Issue 1
Start page 1.1
End page 1.4
Total pages 4
Place of publication London, United Kingdom
Publisher BioMed Central
Collection year 2016
Language eng
Formatted abstract
Background: Genome-wide association studies (GWAS) are an important tool for the mapping of complex traits and diseases. Visual inspection of genomic annotations may be used to generate insights into the biological mechanisms underlying GWAS-identified loci.

Results: We developed LocusTrack, a web-based application that annotates and creates plots of regional GWAS results and incorporates user-specified tracks that display annotations such as linkage disequilibrium (LD), phylogenetic conservation, chromatin state, and other genomic and regulatory elements. Currently, LocusTrack can integrate annotation tracks from the UCSC genome-browser as well as from any tracks provided by the user.

Conclusion: LocusTrack is an easy-to-use application and can be accessed at the following URL: Users can upload and manage GWAS results and select from and/or provide annotation tracks using simple and intuitive menus. LocusTrack scripts and associated data can be downloaded from the website and run locally.
Keyword LocusTrack
Genome-wide association studies (GWAS)
Web based data visualisation
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Medicine Publications
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Citation counts: TR Web of Science Citation Count  Cited 3 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 4 times in Scopus Article | Citations
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