Description Usage Arguments Value Author(s) References See Also Examples
Estimate the covariance matrix of multiple traits based on their (null) summary Z-scores.
1 |
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. |
estimated correlation matrix.
Junghi Kim, Yun Bai and Wei Pan
Junghi Kim, Yun Bai and Wei Pan (2015) An Adaptive Association Test for Multiple Phenotypes with GWAS Summary Statistics, Genetic Epidemiology, 8:651-663
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)
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