Journal
NATURE BIOTECHNOLOGY
Volume 32, Issue 7, Pages 663-+Publisher
NATURE PORTFOLIO
DOI: 10.1038/nbt.2895
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Funding
- US National Institutes of Health [R01 GM104390, R01 DK091374, R01 CA164138, R44HG006579, R01 GM59290]
- University of Luxembourg-Institute for Systems Biology Program
- NHLBI [UO1 HL100406, U01 HL098179]
- NIH [R01 MH094400, R01 MH099134, R00HG005846]
- MD Anderson Cancer Center Odyssey Program
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High-throughput sequencing of related individuals has become an important tool for studying human disease. However, owing to technical complexity and lack of available tools, most pedigree-based sequencing studies rely on an ad hoc combination of suboptimal analyses. Here we present pedigree-VAAST (pVAAST), a disease-gene identification tool designed for high-throughput sequence data in pedigrees. pVAAST uses a sequence-based model to perform variant and gene-based linkage analysis. Linkage information is then combined with functional prediction and rare variant case-control association information in a unified statistical framework. pVAAST outperformed linkage and rare-variant association tests in simulations and identified disease-causing genes from whole-genome sequence data in three human pedigrees with dominant, recessive and de novo inheritance patterns. The approach is robust to incomplete penetrance and locus heterogeneity and is applicable to a wide variety of genetic traits. pVAAST maintains high power across studies of monogenic, high-penetrance phenotypes in a single pedigree to highly polygenic, common phenotypes involving hundreds of pedigrees.
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