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This article is part of the supplement: Genetic Analysis Workshop 17: Unraveling Human Exome Data

Open Access Proceedings

Challenges and directions: an analysis of Genetic Analysis Workshop 17 data by collapsing rare variants within family data

Peng Lin, Michael Hamm, Sarah Hartz, Zhehao Zhang and John P Rice*

Author Affiliations

Department of Psychiatry, Washington University, 660 S. Euclid Ave., Campus Box 8134, St. Louis, MO 63110, USA

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BMC Proceedings 2011, 5(Suppl 9):S30  doi:10.1186/1753-6561-5-S9-S30

Published: 29 November 2011


Recent studies suggest that the traditional case-control study design does not have sufficient power to discover rare risk variants. Two different methods—collapsing and family data—are suggested as alternatives for discovering these rare variants. Compared with common variants, rare variants have unique characteristics. In this paper, we assess the distribution of rare variants in family data. We notice that a large number of rare variants exist only in one or two families and that the association result is largely shaped by those families. Therefore we explore the possibility of integrating both the collapsing method and the family data method. This combinational approach offers a potential power boost for certain causal genes, including VEGFA, VEGFC, SIRT1, SREBF1, PIK3R3, VLDLR, PLAT, and FLT4, and thus deserves further investigation.