## ----load_martini------------------------------------------------------------- library(martini) ## ----create_gi---------------------------------------------------------------- gi <- get_GI_network(minigwas, snpMapping = minisnpMapping, ppi = minippi) ## ----simulate_snps------------------------------------------------------------ causal <- simulate_causal_snps(gi, ngenes = 2, pcausal = 0.3) par(mar=c(0,0,0,0)+.1) plot(gi, mark.groups = names(causal)) ## ----simulate_quantitative_phenotype------------------------------------------ # create a random 100x25 matrix of genotypes X <- lapply(seq_len(100), function(i) { sample(c(0,1,2), 25, replace = TRUE) }) X <- do.call(rbind, X) colnames(X) <- minigwas$map$snp.name rownames(X) <- 1:nrow(X) X <- X + 1 mode(X) <- "raw" minigwas$genotypes <- new("SnpMatrix", X) simulated <- simulate_phenotype(minigwas, snps = causal, h2 = 0.9) ## ----simulate_qualitative_phenotype------------------------------------------- simulated <- simulate_phenotype(minigwas, snps = causal, h2 = 0.9, qualitative = TRUE, ncases = 10, ncontrols = 40, prevalence = 0.2)