# R/asum.R In izhbannikov/vartools: Variant Association Tools R-package

#### Documented in asum

```asum_method <- function(U, V) {
# Internal function for ASUM method
# decreasing order of U
Ords <- order(U/sqrt(diag(V)), decreasing=TRUE)
# Ustd in decreasing order
Uords <- U[Ords]
# ord cov matrix
V.ords <- as.matrix(V[Ords, Ords])

## get scores
k <- length(U)
scores <- scores.ord <- rep(0, k)
pvals <- pvals.ord <- rep(0, k)
for (j in 1:k){
aux <- sum_method(U[1:j], V[1:j,1:j])
scores[j] <- aux[1]
pvals[j] <- aux[2]
aux.ord <- sum_method(Uords[1:j], V.ords[1:j,1:j])
scores.ord[j] <- aux.ord[1]
pvals.ord[j] <- aux.ord[2]
}
p1 <- min(pvals)
p2 <- min(pvals.ord)
S1 <- scores[which(pvals==p1)]
S2 <- scores.ord[which(pvals.ord==p2)]

# Return value
c(S1, p1, S2, p2)
}

asum <- function(table, perm=100) {
y <- as.numeric(as.matrix(table[,1]))
X <- as.matrix(table[,-1])
## checking arguments
Xy_perm <- check_args(y, X, perm)
y <- Xy_perm\$y
X <- Xy_perm\$X
perm <- Xy_perm\$perm

## get U and V
getuv <- getUV(y, as.matrix(X))
U <- getuv\$U
V <- getuv\$V
## run score method
stat.asum <- asum_method(U, V)
asum.stat1 <- stat.asum[1]  # stat normal
p1.asum <- stat.asum[2]     # pval normal

## permutations
perm.pval <- NA
if (perm > 0){
p1.perm <- rep(0, perm)
ymean <- mean(y)
for (i in 1:perm) {
perm.sample <- sample(1:length(y))
# center phenotype y
y.perm <- y[perm.sample] - ymean
# get score vector
U.perm <- colSums(y.perm * X, na.rm=TRUE)
perm.asum <- asum_method(U.perm, V)
p1.perm[i] <- perm.asum[2]
}
# p-value
perm.pval <- sum(p1.perm > p1.asum) / perm   # normal
}

## results
name <- "aSum: Adaptive Sum Test"
arg.spec <- c(sum(y), length(y)-sum(y), ncol(X), perm)
names(arg.spec) <- c("cases", "controls", "variants", "n.perms")
res <- list(asum.stat = asum.stat1,
perm.pval = perm.pval,
args = arg.spec,
name = name)
return(res)
}
```
izhbannikov/vartools documentation built on May 17, 2017, 5:29 a.m.