Power calculations for the transmission/disequilibrium and affected sib pair tests using elementary probability methods.
The transmission/disequilibrium test (TDT) and the affected sib pair test (ASP) both test for the association of a marker allele with some conditions. Here, we present methods for calculating the probability of detecting the association (power) for a study examining a fixed number of families for suitability for the study and for calculating the number of such families to be examined. Both calculations use a genetic model for the association. The model considered posits a bi-allelic marker locus that is linked to a bi-allelic disease locus with a possibly nonzero recombination fraction between the loci. The penetrance of the disease is an increasing function of the number of disease alleles. The TDT tests whether the transmission by a heterozygous parent of a particular allele at a marker locus to an affected offspring occurs with probability greater than 0.5. The ASP tests whether transmission of the same allele to two affected sibs occurs with probability greater than 0.5. In either case, evidence that the probability is greater than 0.5 is evidence for association between the marker and the disease. Study inclusion criteria (IC) can greatly affect the necessary sample size of a TDT or ASP study. IC considered by us include a randomly selected parent at least one parent or both parents required to be heterozygous. It also allows a specified minimum number of affected offspring to be required (TDT only). We use elementary probability calculations rather than complex mathematical manipulations or asymptotic methods (large sample size approximations) to compute power and requisite sample size for a proposed study. The advantages of these methods are simplicity and generality.
Brown
Barry W
BW
Department of Biostatistics and Applied Mathematics, Unit 237, University of Texas M.D. Anderson Cancer Center, Houston, TX 77030, USA. bwb@mdanderson.org
D002874:Chromosome Mapping / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D030342:Genetic Diseases, Inborn / Q000235:genetics*; D015810:Linkage Disequilibrium; D011336:Probability; D035781:Siblings