Power calculations for a general class of family-based association tests: dichotomous traits.

Using large-sample theory, we present a unified approach to power calculations for family-based association tests. Currently available methods for power calculations are restricted to special designs or require approximations or simulations. Our analytical approach to power calculations is broadly applicable in many settings. We discuss power calculations for two scenarios that have high practical relevance and in which power previously could only be assessed by simulation studies or by approximations: (1) studies using both affected and unaffected offspring and (2) studies with missing parental information. When the population prevalence is high, it can be worthwhile to genotype unaffected offspring. For many scenarios, high power can be achieved with reasonable sample sizes, even when no parental information is available.

[1]  J. Ott Statistical properties of the haplotype relative risk , 1989, Genetic epidemiology.

[2]  M Knapp,et al.  A note on power approximations for the transmission/disequilibrium test. , 1999, American journal of human genetics.

[3]  Christoph Lange,et al.  On a general class of conditional tests for family‐based association studies in genetics: the asymptotic distribution, the conditional power, and optimality considerations , 2002, Genetic epidemiology.

[4]  W M Chen,et al.  A general and accurate approach for computing the statistical power of the transmission disequilibrium test for complex disease genes , 2001, Genetic epidemiology.

[5]  M. Boehnke,et al.  Genetic association mapping based on discordant sib pairs: the discordant-alleles test. , 1998, American journal of human genetics.

[6]  Xin Xu,et al.  Implementing a unified approach to family‐based tests of association , 2000, Genetic epidemiology.

[7]  Daniel Rabinowitz,et al.  A Unified Approach to Adjusting Association Tests for Population Admixture with Arbitrary Pedigree Structure and Arbitrary Missing Marker Information , 2000, Human Heredity.

[8]  C. Lewis,et al.  Power comparisons of the transmission/disequilibrium test and sib-transmission/disequilibrium-test statistics. , 1999, American journal of human genetics.

[9]  Genetic epidemiology and microarrays , 2002, Genetic epidemiology.

[10]  N. Laird,et al.  The family based association test method: strategies for studying general genotype–phenotype associations , 2001, European Journal of Human Genetics.

[11]  Christoph Lange,et al.  A multivariate family-based association test using generalized estimating equations: FBAT-GEE. , 2003, Biostatistics.

[12]  W. Ewens,et al.  Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM). , 1993, American journal of human genetics.

[13]  N. Camp,et al.  Genomewide transmission/disequilibrium testing--consideration of the genotypic relative risks at disease loci. , 1997, American journal of human genetics.

[14]  N Risch,et al.  The Future of Genetic Studies of Complex Human Diseases , 1996, Science.

[15]  Thomas G Schulze,et al.  Genetic association mapping at the crossroads: which test and why? Overview and practical guidelines. , 2002, American journal of medical genetics.

[16]  W. Ewens,et al.  A sibship test for linkage in the presence of association: the sib transmission/disequilibrium test. , 1998, American journal of human genetics.

[17]  M. Knapp Using exact P values to compare the power between the reconstruction-combined transmission/disequilibrium test and the sib transmission/disequilibrium test. , 1999, American journal of human genetics.

[18]  Hongyu Zhao Family-based association studies , 2000 .

[19]  N M Laird,et al.  A discordant-sibship test for disequilibrium and linkage: no need for parental data. , 1998, American journal of human genetics.

[20]  N. Risch Searching for genetic determinants in the new millennium , 2000, Nature.