R/synSNP.R

In SMLE: Joint Feature Screening via Sparse MLE

#' Synthetic genetic association study data set
#'
#'  This simulated data set consists of 10,031 genetic variants (SNPs) and a 
#'  continuous response variable measured on 800 individuals. The 
#'  genotypes were sampled from genotypic distributions derived from the  
#'  1000 Genomes project using the \R package \pkg{sim1000G}. The genotype 
#'  is coded as 0, 1, or 2 by counting the number of minor alleles (the allele 
#'  that is less common in the sample). The continuous response variable was 
#'  simulated from a normal distribution with mean that depends additively 
#'  on the causal SNPs. 
#'  
#' @references   
#' The 1000 Genomes Project Consortium (2015). Global reference for human genetic variation,
#'   \emph{Nature}, \bold{526}(7571), 68-74.s
#' @docType data
#'
#' @usage data(synSNP)
#' @format An object of class \code{'data.frame'} with 800 rows and 10,032 columns.
#' @examples
#' \donttest{
#' data(synSNP)
#' Y_SNP <- synSNP[,1]
#' X_SNP <- synSNP[,-1]
#' fit <- SMLE(Y = Y_SNP, X = X_SNP, k = 40)
#' summary(fit)
#' plot(fit)
#' }

"synSNP"