GPC {GeneticsDesign} | R Documentation |
Genetics power calculator for linear trend association studies.
GPC(pA, pD, RRAa, RRAA, r2, pB, nCase=500, ratio=1, alpha=0.05, quiet=FALSE) GPC.default(pA, pD, RRAa, RRAA, Dprime, pB, nCase=500, ratio=1, alpha=0.05, quiet=FALSE)
pA |
High risk allele frequency (A ). |
pD |
Disease prevalence. |
RRAa |
Genotype relative risk (Aa ) = RR(Aa|aa)=Pr(D|Aa)/Pr(D|aa) . |
RRAA |
Genotype relative risk (AA ) = RR(AA|aa)=Pr(D|AA)/Pr(D|aa) . |
r2 |
LD measure. Assume that D>0 . |
Dprime |
LD measure. |
pB |
Marker allele frequency (B ). |
nCase |
Number of cases. |
ratio |
Control:case ratio = nControl/nCase . |
alpha |
User-defined type I error rate. |
quiet |
Print some intermediate results if quiet=FALSE . |
The power is for the test that disease is associated with a marker, given high risk allele frequency (A
), disease prevalence, genotype relative risk (Aa
), genotype relative risk (AA
), LD measure (D'
or r^2
), marker allele frequency (B
), number of cases, control:case ratio, and probability of the Type I error. The linear trend test (Cochran 1954; Armitage 1955) is used.
power |
The estimated power for the association test. |
ncp |
Non-centrality parameter. |
mat.para |
A matrix of case-control parameters, including number of cases, number of controls, high risk allele frequency, prevalence, genotypic relative risk (Aa ), genotypic relative risk (AA ), genotypic risk for aa (baseline). |
mat.B |
A matrix of marker locus B parameters, including marker allele frequency, linkage disequilibrium (D' ), penetrance at marker genotype bb , penetrance at marker genotype Bb , penetrance at marker genotype BB , genotypic odds ratio Bb , genotypic odds ratio BB . |
mat.aFreq |
A 2 by 2 matrix of expected allele frequencies Pr(B|D), Pr(b|D), Pr(B|non D), Pr(b|non D) . |
mat.gFreq |
A 3 by 2 matrix of expected genotype frequencies Pr(BB|D), Pr(Bb|D), Pr(bb|D), Pr(BB|non D), Pr(Bb|non D), Pr(bb|non D) . |
mat.stat |
Power estimates for a sequence of Type I errors. |
Weiliang Qiu stwxq@channing.harvard.edu, Ross Lazarus ross.lazarus@channing.harvard.edu
Armitage, P. (1955) Tests for linear trends in proportions and frequencies. Biometrics, 11, 375-386.
Cochran, W.G. (1954) Some methods for strengthening the common chi-squared tests. Biometrics, 10, 417-451.
Gordon D, Finch SJ, Nothnagel M, Ott J (2002) Power and sample size calculations for case-control genetic association tests when errors are present: application to single nucleotide polymorphisms. Hum. Hered., 54:22-33.
Gordon D, Haynes C, Blumenfeld J, Finch SJ (2005) PAWE-3D: visualizing Power for Association With Error in case/control genetic studies of complex traits. Bioinformatics, 21:3935-3937.
Purcell S, Cherny SS, Sham PC. (2003). Genetic Power Calculator: design of linkage and association genetic mapping studies of complex traits. Bioinformatics, 19(1):149-150.
Sham P. (1998). Statistics in Human Genetics. Arnold Applications of Statistics.
res1<-GPC(pA=0.05, pD=0.1, RRAa=1.414, RRAA=2, r2=0.9, pB=0.06, nCase=500, ratio=1, alpha=0.05, quiet=FALSE) res2<-GPC.default(pA=0.05, pD=0.1, RRAa=1.414, RRAA=2, Dprime=0.9, pB=0.06, nCase=500, ratio=1, alpha=0.05, quiet=FALSE)