Description Usage Arguments Details Value Examples
A function to calculate power for STEPS given a set of parameters
1 | power.STEPS(maf, qntl = 0.1, N, b1, b3, g1)
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maf |
minor allele frequency of SNP, between 0 and 0.5. |
qntl |
quantile to choose y1 and y2, between 0 and 0.5. Default value is 0.1, that is, subjects with primary phenotype of top 10% and bottom 10% are in cohort |
N |
sample size of dataset |
b1 |
parameter to characterize association between genotype and primary trait. See 'Details' for more information. |
b3 |
parameter to characterize association between secondary trait and primary trait. See 'Details' for more information. |
g1 |
parameter to characterize association between genotype and secondary trait. See 'Details' for more information. |
For continuous secondary traits, model
Z = g0+g1*G+0.4*X+e1
Y = b0+b1*G+0.4*X+b3*Z+e2
For binary secondary traits, model
Z = g0+g1*G+0.4*X+e1
D = I(Z>cutoff)
Y = b0+b1*G+0.4*X+b3*Z+e2
where 'Z'/'D' is continuous/binary secondary trait, 'Y' is primary trait, 'X' is covariate following a standard normal distribution, 'G' is genotype following HWE with MAF of 'maf', error term 'e1'/'e2' follows a standard normal distribution, only subjects with primary phenotype at top/bottom quantile of 'qntl' are retained as extreme phenotype sampling design.
An R data frame with powers for both continuous/binary traits and 4 significance levels from 1E-5 to 1E-8.
1 | power.STEPS(maf=0.3,qntl=0.1,N=1000,b1=-0.4,b3=-0.7,g1=0.3)
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