FSTpackage (version 0.1)

FST.SummaryStat.test: Using summary statistics to test the association between an quantitative/dichotomous outcome variable and a gene by a score type test allowing for multiple functional annotation scores.

Description

This function tests a specific gene using summary statistics (score vector and its covariance matrix)

Usage

FST.SummaryStat.test(score,Sigma,Z,weights,B=5000)

Arguments

score

The score vector of length p, where p is the total number of genetic variables.

Sigma

The p*p covariance matrix of the score vector

Z

Functional annotation scores, an p*q matrix where p is the total number of genetic variables and q is the number of functional annotation scores. Note that the first column in Z should be all 1 if the users want the original weights of SKAT/burden test to be included.

weights

A numeric vector of weights for genetic variants (The length should be same as the number of genetic variants in the set.). These weights are usually based on minor allele frequencies.

B

Number of Bootstrap replicates. The default is 5000.

Value

p.value

P-value of the set based generalized score type test.

%% ~Describe the value returned %% If it is a LIST, use %% \item{comp1 }{Description of 'comp1'} %% \item{comp2 }{Description of 'comp2'} %% ...

Examples

## FST.SummaryStat.test tests a region.
# Input: score (a score vector), Sigma (the covariance matrix of the score vector)

library(FSTpackage)

data(FST.example)
score<-FST.example$score;Sigma<-FST.example$Sigma;Z<-FST.example$Z;weights<-FST.example$weights

# test with 5000 bootstrap replicates
result<-FST.SummaryStat.test(score,Sigma,Z,weights,B=5000)