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Type: Package
Title: QTL Genome-Wide Composite Interval Mapping with Graphical User Interface
Version: 2.1.1
Date: 2020-10-8
Author: Zhang Ya-Wen, Wen Yang-Jun, Wang Shi-Bo, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<soyzhang@mail.hzau.edu.cn>
Description: Conduct multiple quantitative trait loci (QTL) mapping under the framework of random-QTL-effect linear mixed model. First, each position on the genome is detected in order to obtain a negative logarithm P-value curve against genome position. Then, all the peaks on each effect (additive or dominant) curve are viewed as potential QTL, all the effects of the potential QTL are included in a multi-QTL model, their effects are estimated by empirical Bayes in doubled haploid population or by adaptive lasso in F2 population, and true QTL are identified by likelihood radio test. See Wen et al. (2018) <doi:10.1093/bib/bby058>.
Encoding: UTF-8
Depends: R (≥ 3.5.0),shiny,MASS,qtl
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Imports: Rcpp (≥ 0.12.17),methods,openxlsx,stringr,data.table,glmnet,doParallel,foreach,QTL.gCIMapping
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2020-10-12 03:08:51 UTC; 亚雯
Repository: CRAN
Date/Publication: 2020-10-12 04:40:12 UTC

QTL Genome-Wide Composite Interval Mapping with Graphical User Interface

Description

Conduct multiple quantitative trait loci (QTL) mapping under the framework of random-QTL-effect mixed linear model. First, each position on the genome is detected in order to construct a negative logarithm P-value curve against genome position. Then, all the peaks on each effect (additive or dominant) curve are viewed as potential QTL, all the effects of the potential QTL are included in a multi-QTL model, their effects are estimated by empirical Bayes in doubled haploid or by adaptive lasso in F2, and true QTL are identified by likelihood radio test.

Usage

QTL.gCIMapping.GUI()

Details

Package: QTL.gCIMapping.GUI
Type: Package
Version: 2.1.1
Date: 2020-10-8
Depends: shiny,MASS,qtl
Imports: methods,openxlsx,stringr,Rcpp
License: GPL version 2 or newer
LazyLoad: yes

Author(s)

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

References

An efficient multi-locus mixed model framework for the detection of small and linked QTLs in F2.Wen Yang-Jun, Zhang Ya-Wen, Zhang Jin, Feng Jian-Ying, Jim M. Dunwell, Zhang Yuan-Ming*

Examples

## Not run: QTL.gCIMapping.GUI()

To perform QTL mapping with wang method

Description

Genome-wide Composite Interval Mapping

Usage

WangF(pheRaw,genRaw,mapRaw1,yygg1,flagRIL,cov_en,Population,WalkSpeed,CriLOD)

Arguments

pheRaw

phenotype matrix.

genRaw

genotype matrix.

mapRaw1

linkage map matrix.

yygg1

the transformed covariate matrix .

flagRIL

if RIL or not.

cov_en

raw covariate matrix.

Population

population flag.

WalkSpeed

Walk speed for Genome-wide Scanning.(WalkSpeed=1).

CriLOD

Critical LOD scores for significant QTL (CriLOD=2.5).

Author(s)

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

Examples

## Not run: 
data(gen)
data(phe)
data(map)
wf<-WangF(pheRaw=phe,genRaw=gen,mapRaw1=map,yygg1=NULL,
flagRIL=0,cov_en=NULL,Population="DH",WalkSpeed=1,CriLOD=2.5)

## End(Not run)

The second step of wang method

Description

Genome-wide Composite Interval Mapping

Usage

WangS(flag,CriLOD,NUM,pheRaw,chrRaw_name,yygg,mx,phe,chr_name,gen,
mapname,CLO)

Arguments

flag

fix or random model.

CriLOD

LOD score.

NUM

The number of trait.

pheRaw

Raw phenotype matrix.

chrRaw_name

raw chromosome name.

yygg

covariate matrix.

mx

raw genotype matrix.

phe

phenotype matrix.

chr_name

chromosome name.

gen

genotype matrix.

mapname

linkage map matrix.

CLO

Number of CPUs.

Author(s)

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

Examples

## Not run: 
data(gen)
data(phe)
data(map)
W1re<-WangF(pheRaw=phe,genRaw=gen,mapRaw1=map,yygg1=NULL,
flagRIL=0,cov_en=NULL,Population="DH",WalkSpeed=1,CriLOD=2.5)
###
ws<-WangS(flag=1,CriLOD=2.5,NUM=1,pheRaw=phe,
chrRaw_name=W1re$chrRaw_name,yygg=W1re$yygg,mx=W1re$mx,
phe=W1re$phe,chr_name=W1re$chr_name,gen=W1re$gen,
mapname=W1re$mapname,CLO=1)

## End(Not run)

To perform QTL mapping with Wen method

Description

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

Usage

WenF(pheRaw,genRaw,mapRaw1,yygg1,cov_en,WalkSpeed,CriLOD,dir)

Arguments

pheRaw

phenotype matrix.

genRaw

genotype matrix.

mapRaw1

linkage map matrix.

yygg1

the transformed covariate matrix .

cov_en

raw covariate matrix.

WalkSpeed

Walk speed for Genome-wide Scanning.(WalkSpeed=1).

CriLOD

Critical LOD scores for significant QTL (CriLOD=2.5).

dir

file path in your computer.

Author(s)

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

Examples

## Not run: 
data(genf2)
data(phef2)
data(mapf2)
wf<-WenF(pheRaw=phef2,genRaw=genf2,mapRaw1=mapf2,
yygg1=NULL,cov_en=NULL,WalkSpeed=1,CriLOD=2.5,dir=tempdir())

## End(Not run)

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,setseed,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.

setseed

random seed set in which, the cross validation is needed.

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, Zhang Yuan-Ming
Maintainer: Yuanming Zhang<soyzhang@mail.hzau.edu.cn>

Examples

## Not run: 
data(genf2)
data(phef2)
data(mapf2)
WEN1re<-WenF(pheRaw=phef2,genRaw=genf2,mapRaw1=mapf2,
yygg1=NULL,cov_en=NULL,WalkSpeed=1,CriLOD=2.5,dir=tempdir())
###
ws<-WenS(flag=1,CriLOD=2.5,NUM=1,pheRaw=phef2,
Likelihood="REML",setseed=11001,flagrqtl=FALSE,
yygg=WEN1re$yygg,mx=WEN1re$mx,phe=WEN1re$phe,
chr_name=WEN1re$chr_name,v.map=WEN1re$v.map,
gen.raw=WEN1re$gen.raw,a.gen.orig=WEN1re$a.gen.orig,
d.gen.orig=WEN1re$d.gen.orig,n=WEN1re$n,
names.insert2=WEN1re$names.insert2,
X.ad.tran.data=WEN1re$X.ad.tran.data,
X.ad.t4=WEN1re$X.ad.t4,dir=tempdir())

## End(Not run)

genotype example data

Description

GCIM format of DH genotype dataset.

Usage

  data(gen)

Details

Dataset input of file for WangF function.

Author(s)

Maintainer: Yuanming Zhang<soyzhang@mail.hzau.edu.cn>


genotype example data

Description

GCIM format of F2 genotype dataset.

Usage

  data(genf2)

Details

Dataset input of file for WenF function.

Author(s)

Maintainer: Yuanming Zhang<soyzhang@mail.hzau.edu.cn>


map example data

Description

GCIM format of DH map dataset.

Usage

  data(map)

Details

Dataset input of file for WangF function.

Author(s)

Maintainer: Yuanming Zhang<soyzhang@mail.hzau.edu.cn>


map example data

Description

GCIM format of F2 map dataset.

Usage

  data(mapf2)

Details

Dataset input of file for WenF function.

Author(s)

Maintainer: Yuanming Zhang<soyzhang@mail.hzau.edu.cn>


To insert marker in genotype.

Description

a method that can insert marker in genotype.

Usage

markerinsert(mp,geno,map,cl,gg1,gg2,gg0,flagRIL)

Arguments

mp

linkage map matrix after insert.

geno

genotype matrix.

map

linkage map matrix.

cl

walk speed.

gg1

raw covariate matrix.

gg2

code for type 1.

gg0

code for missing.

flagRIL

RIL population or not.

Author(s)

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

Examples

## Not run: 
mp<-matrix(c(197.9196,198.7536,199.5876,200.4216,201.2453,
202.0691,202.8928,203.7521,204.6113,205.4706,206.3298,207.1891,
1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,3,3,3,3,3,3,
1,1,1,2,2,2,3,3,3,3,3,3,1,2,3,4,5,6,7,8,9,10,11,12),12,5)
map<-matrix(c(1,1,1,1,197.9196,200.4216,202.8928,207.1891),4,2)
geno<-matrix(c(1,99,99,99),1,4)
mark_insert<-QTL.gCIMapping::markerinsert(mp,geno,map,cl=1,gg1=1,gg2=-1,
gg0=99,flagRIL=1)

## End(Not run)

phenotype example data

Description

GCIM format of DH phenotype dataset.

Usage

  data(phe)

Details

Dataset input of file for WangF function.

Author(s)

Maintainer: Yuanming Zhang<soyzhang@mail.hzau.edu.cn>


phenotype example data

Description

GCIM format of F2 phenotype dataset.

Usage

  data(phef2)

Details

Dataset input of file for WenF function.

Author(s)

Maintainer: Yuanming Zhang<soyzhang@mail.hzau.edu.cn>

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.