title: Family-based association tests for sequence data, and comparisons with population-based association tests.
abstract: Recent advances in high-throughput sequencing technologies make it increasingly more efficient to sequence large cohorts for many complex traits. We discuss here a class of sequence-based association tests for family-based designs that corresponds naturally to previously proposed population-based tests, including the classical Burden and variance-component tests. This framework allows for a direct comparison between the powers of sequence-based association tests with family- vs population-based designs. We show that for dichotomous traits using family-based controls results in similar power levels as the population-based design (although at an increased sequencing cost for the family-based design), while for continuous traits (in random samples, no ascertainment) the population-based design can be substantially more powerful. A possible disadvantage of population-based designs is that they can lead to increased false-positive rates in the presence of population stratification, while the family-based designs are robust to population stratification. We show also an application to a small exome-sequencing family-based study on autism spectrum disorders. The tests are implemented in publicly available software.
authors: Department of Biostatistics, Columbia University, New York, NY, USA.
authors: Iuliana
authors: I
authors: Ionita-Laza
authors: Seunggeun
authors: S
authors: Lee
authors: Vladimir
authors: V
authors: Makarov
authors: Joseph D
authors: JD
authors: Buxbaum
authors: Xihong
authors: X
authors: Lin
mesh_terms: D002659:Child Development Disorders, Pervasive / Q000235:genetics; D059472:Exome; D056726:Genetic Association Studies / Q000379:methods*; D006801:Humans; D010375:Pedigree; D011153:Population / Q000235:genetics*; D012680:Sensitivity and Specificity; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software
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