minMAFeQTL.sLR: Minimum Detectable Minor Allele Frequencey Calculation for...
In sterding/powerEQTL: Power and Sample Size Calculation for eQTL Analysis

Description Usage Arguments Details Value Author(s) References See Also Examples

Minimum detectable minor allele frequency (MAF) calculation for eQTL analysis that tests if a SNP is associated to a gene probe by using simple linear regression.

minMAFeQTL.SLR(slope,
               typeI = 0.05,
               nTests = 200000,
               myntotal = 200,
               mypower = 0.8,
               mystddev = 0.13,
               verbose = TRUE)

`slope`	Slope of the simple linear regression.
`typeI`	Type I error rate for testing if a SNP is associated to a gene probe.
`nTests`	integer. Number of tests in eQTL analysis.
`myntotal`	integer. Number of subjects.
`mypower`	Desired power for the eQTL analysis.
`mystddev`	Standard deviation of the random error term epsilon in simple linear regression.
`verbose`	logic. indicating if intermediate results should be output.

To test if a SNP is associated with a gene probe, we use the simple linear regression

y_i = beta_0 + beta_1 * x_i + epsilon_i,

where y_i is the gene expression level of the i-th subject, x_i is the genotype of the i-th subject, and ε_i is the random error term. Additive coding for genotype is used. To test if the SNP is associated with the gene probe, we test the null hypothesis H_0: beta_1 = 0.

Denote p as the minor allele frequency (MAF) of the SNP. Under Hardy-Weinberg equilibrium, we can calculate the variance of genotype of the SNP: sigma^2_x = 2 * p * (1 - p), where sigma^2_x is the variance of the predictor (i.e. the SNP) x_i.

We then can use Dupont and Plummer's (1998) power/sample size calculation formula to calculate the minimum detectable slope, adjusting for multiple testing.

The estimated minimum detectable MAF.

Xianjun Dong <XDONG@rics.bwh.harvard.edu>, Tzuu-Wang Chang <Chang.Tzuu-Wang@mgh.harvard.edu>, Scott T. Weiss <restw@channing.harvard.edu>, Weiliang Qiu <stwxq@channing.harvard.edu>

Dupont, W.D. and Plummer, W.D.. Power and Sample Size Calculations for Studies Involving Linear Regression. Controlled Clinical Trials. 1998;19:589-601.

powerEQTL.SLR, ssEQTL.SLR

minMAFeQTL.SLR(slope = 0.1299513,
               typeI = 0.05,
               nTests = 200000,
               myntotal = 176,
               mypower = 0.8,
               mystddev = 0.13,
               verbose = TRUE)