XTRA 2 {bWGR}R Documentation

Additional tools

Description

Complementary functions that may help with handling parameters and routine operations.

Details

emGWA(y,gen) # Simple MLM for association analysis

markov(gen,chr=NULL) # Markovian imputation of genotypes coded as 012

IMP(X) # Imputes genotypes with SNP expectation (column average)

CNT(X) # Recodes SNPs by centralizing columns in a matrix

GAU(X) # Creates Gaussian kernel as exp(-Dist2/mean(Dist2))

GRM(X,Code012=FALSE) # Creates additive kinship matrix VanRaden (2008)

SPC(y,blk,row,col,rN=3,cN=1) # Spatial covariate

SPM(blk,row,col,rN=3,cN=1) # Spatial design matrix

SibZ(id,p1,p2) # Pedigree design matrix compatible to regression methods

Hmat(ped,gen=NULL) # Kinship combining pedigree and genomics

EigenGRM(X, centralizeZ = TRUE, cores = 2) # GRM using Eigen library

EigenARC(X, centralizeZ = TRUE, cores = 2) # ArcCosine kernel

EigenGAU(X, phi = 1.0, cores = 2) # Gaussian kernel using Eigen library

EigenCNT(X, cores = 2) # Center SNPs without missing Eigen library

EigenEVD(A, cores = 2) # Eigendecomposition from Eigen library

EigenBDCSVD(X, cores = 2) # BDC single value composition from Eigen

EigenJacobiSVD(X, cores = 2) # Jacobi single value composition from Eigen

EigenAcc(X1, X2, h2 = 0.5, cores = 2) # Deterministic accuracy X1 -> X2

EigenArcZ(Zfndr, Zsamp, cores = 2) # Reduced rank ArcCos kernel PCs with founder rotation

EigenGauZ(Zfndr, Zsamp, phi=1, cores = 2) # Reduced rank Gaussian kernel PCs with founder rotation

K2X(K) # Reparametrize kernel to PCs to run regression models

SimY(Z,k=5,h2=0.5,GC=0.5,seed=123,unbalanced=FALSE) # Simulate Y for multiple environments

MvSimY(Ufndr,Zfndr,Zsamp,GxY,GxL,H2plot,nLoc=20,Seed=123) # Simulate traits given founders

Author(s)

Alencar Xavier


[Package bWGR version 2.2.5 Index]