Power for Association With Error

The name of this program is PAWE, which stands for Power for Association With Errors. Because it has been previously documented (Mote and Anderson 1965; Gordon et al. 2002) that genotyping errors can substantially decrease the asymptotic power to detect association between a trait locus and a marker locus, the purpose of the PAWE program is two fold: (i) to compute power and sample size calculations for genetic case-control association studies in the presence of genotyping errors, and (ii) to determine quantitatively how much, in terms of decrease in asymptotic power for a fixed sample size, or increase in sample size to maintain constant asymptotic power, genotyping errors cost the researcher performing genetic association studies with cases and controls. Thus, results from the PAWE program will be either asymptotic power or sample size values. We note that the results we obtain for data without errors are identical to the results obtained by other genetic association test power calculators, for example the Genetic Power Calculator for case-control studies of discrete traits developed by authors Purcell and Sham.

This program is designed to perform asymptotic power and sample size calculations for genetic case-control studies with a di-allelic locus (for example, a SNP) in the presence of errors. The test statistics considered are the standard chi-square statistics for allelic and genotypic associations. It is assumed that there is a di-allelic trait locus for a discrete trait with two alleles: a wild-type allele or low risk allele, denoted by +, and a trait or high-risk allele, denoted by d. Also, it is assumed that there is a marker locus with two alleles, denoted by 1 and 2.

PAWE version 1.2 February 2003 Written by Derek Gordon Assisted by Michael Nothnagel Run PAWE The name of this program is PAWE, which stands for Power for Association With Errors. Because it has been previously documented (Mote and Anderson 1965; Gordon et al. 2002) that genotyping errors can substantially decrease the asymptotic power to detect association between a trait locus and a marker locus, the purpose of the PAWE program is two fold: (i) to compute power and sample size calculations for genetic case-control association studies in the presence of genotyping errors, and (ii) to determine quantitatively how much, in terms of decrease in asymptotic power for a fixed sample size, or increase in sample size to maintain constant asymptotic power, genotyping errors cost the researcher performing genetic association studies with cases and controls. Thus, results from the PAWE program will be either asymptotic power or sample size values. We note that the results we obtain for data without errors are identical to the results obtained by other genetic association test power calculators, for example the Genetic Power Calculator for case-control studies of discrete traits developed by authors Purcell and Sham. This program is designed to perform asymptotic power and sample size calculations for genetic case-control studies with a di-allelic locus (for example, a SNP) in the presence of errors. The test statistics considered are the standard chi-square statistics for allelic and genotypic associations. It is assumed that there is a di-allelic trait locus for a discrete trait with two alleles: a wild-type allele or low risk allele, denoted by +, and a trait or high-risk allele, denoted by d. Also, it is assumed that there is a marker locus with two alleles, denoted by 1 and 2. Please cite the following two references when reporting results using PAWE: Gordon D., Finch S.J., Nothnagel M., and Ott J. (2002) Power and sample size calculations for case-control genetic association tests when errors present: application to single nucleotide polymorphisms. Human Heredity 54:22-33 Gordon D., Levenstien M.A., Finch S.J., and Ott J. (2003) Errors and linkage disequilibrium interact multiplicatively when computing sample sizes for genetic case-control association studies. Pacific Symposium on Biocomputing: 490-501. Pawe-3D Pawe-PH Pawe Prints Run PAWE

	PAWE is maintained by Chad Haynes Laboratory of Statistical Genetics The Rockefeller University