## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#",
  fig.width=7,
  fig.height=5
)
library(knitr)

## ----load_dependencies, message=FALSE-----------------------------------------
library(mvMAPIT)

## ----simulate_genotypes, eval = FALSE-----------------------------------------
# set.seed(1234)
# 
# n_samples <- 2938
# n_snp <- 5747
# 
# maf <- 0.05 + 0.45 * runif(n_snp)
# random_minor_allele_counts   <- (runif(n_samples * n_snp) < maf) + (runif(n_samples * n_snp) < maf)
# genotype_data <- matrix(random_minor_allele_counts,
#   nrow = n_samples,
#   ncol = n_snp,
#   byrow = TRUE,
# )
# 
# sample_names <- seq_len(n_samples) %>% sprintf(fmt = "id%04d")
# snp_names <- seq_len(n_snp) %>% sprintf(fmt = "snp%04d")
# 
# colnames(genotype_data) <- snp_names
# rownames(genotype_data) <- sample_names

## ----simulation_parameters, eval = FALSE--------------------------------------
# seed <- 67132
# d <- 2
# PVE <- 0.6
# rho <- 0.2
# n_causal <- 1000
# n_trait_specific <- 0
# n_pleiotropic <- 10
# group_ratio_pleiotropic <- 1
# epistatic_correlation <- 0.9
# maf <- 0.05
# simulated_data <- simulate_traits(
#     genotype_data,
#     n_causal = n_causal,
#     n_trait_specific = n_trait_specific,
#     n_pleiotropic = n_pleiotropic,
#     d = d,
#     H2 = PVE,
#     rho = rho,
#     epistatic_correlation = epistatic_correlation,
#     group_ratio_pleiotropic = group_ratio_pleiotropic,
#     maf_threshold = maf,
#     seed = seed
# )