## ----start-------------------------------------------------------------------- library(ASSET) ## ----data file---------------------------------------------------------------- datafile <- system.file("sampleData", "vdata.rda", package="ASSET") ## ----load data---------------------------------------------------------------- load(datafile) data1[1:5, ] SNPs <- paste("SNP", 1:3, sep="") nSNP <- length(SNPs) studies <- paste("STUDY", 1:4, sep="") nStudy <- length(studies) ## ----ncase ncontrol----------------------------------------------------------- case <- matrix(data=NA, nrow=nSNP, ncol=nStudy) control <- matrix(data=NA, nrow=nSNP, ncol=nStudy) for (i in 1:nStudy) { data <- eval(parse(text=paste("data", i, sep=""))) caseVec <- data[, "CC"] == 1 controlVec <- !caseVec for (j in 1:nSNP) { temp <- !is.na(data[, SNPs[j]]) case[j, i] <- sum(caseVec & temp, na.rm=TRUE) control[j, i] <- sum(controlVec & temp, na.rm=TRUE) } } case control ## ----log reg------------------------------------------------------------------ beta <- matrix(data=NA, nrow=nSNP, ncol=nStudy) sigma <- matrix(data=NA, nrow=nSNP, ncol=nStudy) for (i in 1:nStudy) { data <- eval(parse(text=paste("data", i, sep=""))) for (j in 1:nSNP) { data[, "SNP"] <- data[, SNPs[j]] fit <- glm(CC ~ AGE + SNP, data=data, family=binomial()) coef <- summary(fit)$coefficients beta[j, i] <- coef["SNP", 1] sigma[j, i] <- coef["SNP", 2] } } beta sigma ## ----h.traits----------------------------------------------------------------- res <- h.traits(SNPs, studies, beta, sigma, case, control, meta=TRUE) ## ----summary table------------------------------------------------------------ h.summary(res) ## ----subset function---------------------------------------------------------- sub.def <- function(logicalVec) { sum <- sum(logicalVec) ret <- all(logicalVec[1:sum]) ret } ## ----h.traits 2--------------------------------------------------------------- res <- h.traits(SNPs, studies, beta, sigma, case, control, meta=TRUE, zmax.args=list(sub.def=sub.def), pval.args=list(sub.def=sub.def)) ## ----summary table 2---------------------------------------------------------- h.summary(res) ## ----combine data------------------------------------------------------------- data <- NULL for (i in 1:nStudy) { temp <- eval(parse(text=paste("data", i, sep=""))) temp[, "STUDY"] <- i data <- rbind(data, temp) } ## ----dummy vars--------------------------------------------------------------- for (i in 1:nStudy) { dvar <- paste("STUDY_", i, sep="") data[, dvar] <- as.numeric(data[, "STUDY"] %in% i) } ## ----variables---------------------------------------------------------------- snp.vars <- paste("SNP", 1:3, sep="") adj.vars <- c("AGE", "STUDY_1", "STUDY_2", "STUDY_3") types.lab <- paste("TYPE_", 1:3, sep="") ## ----h.types------------------------------------------------------------------ ret <- h.types(data, "TYPE", snp.vars, adj.vars, types.lab, "CONTROL", logit=TRUE) ## ----h.types summary---------------------------------------------------------- h.summary(ret) ## ----sessionInfo-------------------------------------------------------------- sessionInfo()