estcov: estcov

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

Description

Estimate the covariance matrix of multiple traits based on their (null) summary Z-scores.

Usage

1
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

MTaSPUs minP

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
# -- 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)

aSPU documentation built on May 1, 2019, 7:04 p.m.