The overarching goal of this proposal is to produce a single deliverable: VAAST+, which will provide innovative and improved solutions for three major bottlenecks in analyses of personal genomes data: variant prioritization, risk assessment and disease-gene finding. Better variant prioritization and risk assessment will aid diagnostic laboratories and clinicians seeking to interpret the impact of rare variants discovered in the course of routine genetic testing;whereas a better tool for disease-gene finding will empower researchers seeking to employ whole-genome and exome sequences to identify novel genes and disease-causing alleles responsible for rare and common diseases. VAAST+ will leverage the VAAST platform, which was developed with support from an NHGRI Grand Opportunity Grant entitled Tool for annotation and analyses of human whole-genome sequence variation data. Doing so will allow us to rapidly implement VAAST+ and distribute it to the research community.

Public Health Relevance

Whole-genome and exome sequencing, as well as sequence?based clinical diagnostics are increasingly uncovering rare and novel variants that may or may not impact patient health. The overarching goal of this proposal is to produce a single deliverable: VAAST+, which will provide basic researchers, clinical diagnostics laboratories and clinical geneticists with the means to rapidly identify and characterize disease-causing variants;thus bringing sequence data one step closer to the bed-side. VAAST+ will do so by providing innovative solutions to the three principal bottlenecks in healthcare-focused genome analyses today: variant prioritization, risk assessment, and disease-gene finding.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM104390-01
Application #
8431204
Study Section
Special Emphasis Panel (ZGM1-GDB-7 (CP))
Program Officer
Krasnewich, Donna M
Project Start
2013-09-01
Project End
2017-08-31
Budget Start
2013-09-01
Budget End
2014-08-31
Support Year
1
Fiscal Year
2013
Total Cost
$516,603
Indirect Cost
$146,146
Name
University of Utah
Department
Genetics
Type
Schools of Medicine
DUNS #
009095365
City
Salt Lake City
State
UT
Country
United States
Zip Code
84112
Kennedy, Brett; Kronenberg, Zev; Hu, Hao et al. (2014) Using VAAST to Identify Disease-Associated Variants in Next-Generation Sequencing Data. Curr Protoc Hum Genet 81:6.14.1-6.14.25
Campbell, Michael S; Holt, Carson; Moore, Barry et al. (2014) Genome Annotation and Curation Using MAKER and MAKER-P. Curr Protoc Bioinformatics 48:4.11.1-4.11.39
Domyan, Eric T; Guernsey, Michael W; Kronenberg, Zev et al. (2014) Epistatic and combinatorial effects of pigmentary gene mutations in the domestic pigeon. Curr Biol 24:459-64
Hu, Hao; Roach, Jared C; Coon, Hilary et al. (2014) A unified test of linkage analysis and rare-variant association for analysis of pedigree sequence data. Nat Biotechnol 32:663-9
Singleton, Marc V; Guthery, Stephen L; Voelkerding, Karl V et al. (2014) Phevor combines multiple biomedical ontologies for accurate identification of disease-causing alleles in single individuals and small nuclear families. Am J Hum Genet 94:599-610