estcov {aSPU} | R Documentation |
estcov
Description
Estimate the covariance matrix of multiple traits based on their (null) summary Z-scores.
Usage
estcov(allZ, Ps = FALSE)
Arguments
allZ |
matrix of summary Z-scores for all SNP. each row for SNP; each column for single trait. |
Ps |
TRUE if input is p-value, FALSE if input is Z-scores. The default is FALSE. |
Value
estimated correlation matrix.
Author(s)
Junghi Kim, Yun Bai and Wei Pan
References
Junghi Kim, Yun Bai and Wei Pan (2015) An Adaptive Association Test for Multiple Phenotypes with GWAS Summary Statistics, Genetic Epidemiology, 8:651-663
See Also
Examples
# -- n.snp: number of SNPs
# -- n.trait: number of traits
# -- n.subject: number of subjects
n.snp <- 100
n.traits <- 10
n.subjects <- 1000
traits <- matrix(rnorm(n.subjects*n.traits), n.subjects, n.traits)
v <- cov(traits)
allZ <- rmvnorm(n.snp, Sigma=v)
colnames(allZ) <- paste("trait", 1:n.traits, sep="")
rownames(allZ) <- paste("snp", 1:n.snp, sep="")
r <- estcov(allZ)
MTaSPUs(Z = allZ, v = r, B = 100, pow = c(1:4, Inf), transform = FALSE)
MTaSPUs(Z = allZ[1,], v = r, B = 100, pow = c(1:4, Inf), transform = FALSE)
minP(Zi= allZ[1,], r = r)
[Package aSPU version 1.50 Index]