A unified test of linkage analysis and rare-variant association for analysis of pedigree sequence data.

Hu H1, Roach JC2, Coon H3, Guthery SL4, Voelkerding KV5, Margraf RL6, Durtschi JD6, Tavtigian SV7, Shankaracharya1, Wu W8, Scheet P1, Wang S9, Xing J9,Glusman G2, Hubley R2, Li H2, Garg V10, Moore B8, Hood L2, Galas DJ11, Srivastava D12, Reese MG13, Jorde LB8, Yandell M8, Huff CD1.

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Abstract

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.