sommer (version 2.9)

score.calc: Score calculation for markers

Description

This function is a wrapper from the rrBLUP package to be used when a mixed model including markers to perform GWAS is specified and once the variance components have been estimated the fixed effects are obtained as B= (X'V-X)-X'V-y and the score calculation is obtained with the F statistic as F = Beta^2 / Var(Beta) where Var(Beta) = SSe/(n-p) * [XH-X']-, and quantile value for the beta distribution is calculated as q = (n-p) / (n-p + 1 * F) which once obtained, the -log10 for such value is the score value.

Usage

score.calc(marks,y,Z,X,K,ZZ,M,Hinv,ploidy,model,min.MAF,
           max.geno.freq,silent=FALSE,P3D=TRUE, method="NR")

Arguments

marks

marker names

y

response variable

Z

incidence matrix of random effects

X

incidence matrix X as full rank from eigen decomposition

K

covariance structure for random effects

ZZ

incidence matrix of random effects

M

marker matrix

Hinv

inverse of the phenotypic variance matrix

ploidy

numeric value of ploidy level, i.e. 2

model

model for GWAS

min.MAF

minimum minor allele frequency

max.geno.freq

1 - min.MAF

silent

a TRUE/FALSE value indicating if the progress bar should be drawn or not

P3D

when the user performs GWAS, P3D=TRUE means that the variance components are estimated by REML only once, without any markers in the model. When P3D=FALSE, variance components are estimated by REML for each marker separately. The default is the first case.

method

one of the four methods to estimate variance components.

Value

$score

a vector with the -log10(p-values) for the marker effects in the trait under study

See Also

The core functions of the package mmer and mmer2

Examples

# NOT RUN {
# it works internally in the \code{\link{mmer}} function
# }