WenS {QTL.gCIMapping}R Documentation

The second step of Wen method

Description

An efficient multi-locus mixed model framework for the detection of small and linked QTLs in F2

Usage

WenS(flag,CriLOD,NUM,pheRaw,Likelihood,flagrqtl,yygg,mx,phe,chr_name,v.map,
     gen.raw,a.gen.orig,d.gen.orig,n,names.insert2,X.ad.tran.data,X.ad.t4,dir)

Arguments

flag

random or fix model.

CriLOD

LOD score.

NUM

the number of trait.

pheRaw

raw phenotype matrix .

Likelihood

likelihood function.

flagrqtl

do CIM or not.

yygg

covariate matrix.

mx

raw genotype matrix.

phe

phenotype matrix.

chr_name

chromosome name.

v.map

linkage map matrix.

gen.raw

raw genotype matrix.

a.gen.orig

additive genotype matrix.

d.gen.orig

dominant genotype matrix.

n

number of individual.

names.insert2

linkage map after insert.

X.ad.tran.data

genotype matrix after insert.

X.ad.t4

genotype matrix.

dir

file storage path.

Author(s)

Zhang Ya-Wen, Wen Yang-Jun, Wang Shi-Bo, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<soyzhang@mail.hzau.edu.cn>

Examples

F2=data(F2data)
readraw<-Readdata(file=F2data,fileFormat="GCIM",fileICIMcov=NULL)
DoResult<-Dodata(fileFormat="GCIM",Population="F2",Model="Random",readraw)
WEN1re<-WenF(DoResult$pheRaw,DoResult$genRaw,DoResult$mapRaw1,
DoResult$yygg1,DoResult$cov_en,WalkSpeed=1,CriLOD=2.5,
dir=tempdir())
WenS(DoResult$flag,CriLOD=2.5,NUM=1,DoResult$pheRaw,Likelihood="REML",
flagrqtl=FALSE,WEN1re$yygg,WEN1re$mx,WEN1re$phe,WEN1re$chr_name,
WEN1re$v.map,WEN1re$gen.raw,WEN1re$a.gen.orig,WEN1re$d.gen.orig,
WEN1re$n,WEN1re$names.insert2,WEN1re$X.ad.tran.data,WEN1re$X.ad.t4,
dir=tempdir())

[Package QTL.gCIMapping version 3.2 Index]