Biology Faculty Articles
Document Type
Article
Publication Date
11-5-2014
Publication Title
GigaScience
Keywords
AIDS, HIV, Complex diseases, Genome-wide association studies (GWAS), Whole genome sequencing (WGS)
ISSN
2047-217X
Volume
3
Issue/No.
18
First Page
1
Last Page
10
Abstract
Background: As genome-wide sequence analyses for complex human disease determinants are expanding, it is increasingly necessary to develop strategies to promote discovery and validation of potential disease-gene associations.
Findings: Here we present a dynamic web-based platform – GWATCH – that automates and facilitates four steps in genetic epidemiological discovery: 1) Rapid gene association search and discovery analysis of large genome-wide datasets; 2) Expanded visual display of gene associations for genome-wide variants (SNPs, indels, CNVs), including Manhattan plots, 2D and 3D snapshots of any gene region, and a dynamic genome browser illustrating gene association chromosomal regions; 3) Real-time validation/replication of candidate or putative genes suggested from other sources, limiting Bonferroni genome-wide association study (GWAS) penalties; 4) Open data release and sharing by eliminating privacy constraints (The National Human Genome Research Institute (NHGRI) Institutional Review Board (IRB), informed consent, The Health Insurance Portability and Accountability Act (HIPAA) of 1996 etc.) on unabridged results, which allows for open access comparative and meta-analysis.
Conclusions: GWATCH is suitable for both GWAS and whole genome sequence association datasets. We illustrate the utility of GWATCH with three large genome-wide association studies for HIV-AIDS resistance genes screened in large multicenter cohorts; however, association datasets from any study can be uploaded and analyzed by GWATCH.
Additional Comments
Russian Ministry of Science grant #: 11.G34.31.0068; National Institute of Child Health and Human Development grant #: R01-HD-41224; National Eye Institute grant #s: U10EY008052, U10EY008057, U10EY008067
NSUWorks Citation
Svitin, Anton; Sergey Malov; Nikolay Cherkasov; Paul Geerts; Mikhail Rotkevich; Pavel Dobrynin; Andrey Shevchenko; Li Guan; Jennifer L. Troyer; Sher L. Hendrickson; Holli Hutcheson Dilks; T. K. Oleksyk; Sharyne Donfield; Edward Gomperts; Douglas A. Jabs; Efe Sezgin; Mark Van Natta; P. Richard Harrigan; Zabrina L. Brumme; and Stephen J. O'Brien. 2014. "GWATCH: A Web Platform for Automated Gene Association Discovery Analysis." GigaScience 3, (18): 1-10. https://nsuworks.nova.edu/cnso_bio_facarticles/738
ORCID ID
0000-0001-7353-8301
ResearcherID
N-1726-2015
Included in
Computer Sciences Commons, Genetics and Genomics Commons, Medicine and Health Sciences Commons
Comments
© 2014 Svitin et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.