GCA: Genetic Connectedness Analysis

#' Cattle dataset with simulated management units
#'
#' The cattle dataset is simulated with QMSim software (Sargolzaei and Schenkel, 2009).   
#' This dataset includes 2,500 individuals across six generations (from founder to generation 5), 
#' each with 10,000 single nucleotide polymorphisms spread over 29 autosomes. Single phenotype with heritability of 0.6 was simulated.
#' In addition, six fixed effects including one cluster effect and 5 management unit simulation scenarios were simulated. 
#' Fixed effect of the cluster is simulated using the K-medoid algorithm (Kaufman and Rousseeuw, 1990) to assign 2,500 individuals into eight clusters. 
#' MUSC1 is simulated by randomly allocating eight clusters into two sets, which is regarded as the least connected design. From MUSC2 to 5,  
#' randomly sampled individuals (i.e., 140, 210, 280, and 350) were exchanged between the two sets in MUSC1 to steadily increase 
#' the degree of relatedness. 
#'
#' @docType data
#' @name CattleSIM
#' @keywords datasets
#' @usage 
#' data(CattleSIM)
#' 
#' @author Haipeng Yu and Gota Morota 
#' 
#' Maintainer: Haipeng Yu \email{haipengyu@@vt.edu}
#'
#' @example man/examples/CattleSIM.R 
#' @references Sargolzaei, M., and F. S. Schenkel. 2009. Qmsim: a large-scale
#'   genome simulator for livestock. Bioinformatics 25:680–681. doi:10.1093/bioinformatics/btp045
#' @references Kaufman, L. and P. Rousseeuw. 1990. Finding groups in data: 
#' an introduction to cluster analysis. John Wiley and Sons, New York.
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