pvalues: Compute P-values Based on Jonckheere-Terpstra Test Statistics

In fastJT: Efficient Jonckheere-Terpstra Test Statistics for Robust Machine Learning and Genome-Wide Association Studies

Description

Method to compute the p-values for results from fastJT. fastJT must be run with standardized=TRUE in order to use this function.

Usage

pvalues(object)  	

Arguments

object

A fastJT object that is the return of method fastJT. Required.

Value

A matrix of p-values with the same dimensions as the standardized statistics from fastJT.

See Also

fastJT

Examples

# Generate dummy data	
num_patient <- 100
num_marker 	<- 10
num_SNP     <- 500
set.seed(12345)
Mark <- matrix(rnorm(num_patient*num_marker), num_patient, num_marker)
Geno <- matrix(rbinom(num_patient*num_SNP, 2, 0.5), num_patient, num_SNP)
colnames(Mark) <- paste0("Mrk:",1:num_marker)
colnames(Geno) <- paste0("SNP:",1:num_SNP)

res <- fastJT(Y=Mark, X=Geno, outTopN=5)
pvalues(res)
res <- fastJT(Y=Mark, X=Geno, outTopN=NA)
pvalues(res)

fastJT documentation built on Aug. 15, 2017, 1:01 a.m.