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

  • Author(s): Hu, H
  • Roach, JC
  • Coon, H
  • Guthery, SL
  • Voelkerding, KV
  • Margraf, RL
  • Durtschi, JD
  • Tavtigian, SV
  • Shankaracharya
  • Wu, W
  • Scheet, P
  • Wang, S
  • Xing, J
  • Glusman, G
  • Hubley, R
  • Li, H
  • Garg, V
  • Moore, B
  • Hood, L
  • Galas, DJ
  • Srivastava, D
  • Reese, MG
  • Jorde, LB
  • Yandell, M
  • Huff, CD
  • et al.

Published Web Location

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4157619/
No data is associated with this publication.
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. © 2014 Nature America, Inc.

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