FST.SummaryStat.test: Using summary statistics to test the association between an...

In FSTpackage: Unified Sequence-Based Association Tests 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.

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)

Example output

Loading required package: CompQuadForm
Loading required package: SKAT
Loading required package: Matrix
Loading required package: MASS
Loading required package: mvtnorm

FSTpackage documentation built on May 2, 2019, 2:09 a.m.