| Type: | Package |
| Title: | Multi-Locus Random-SNP-Effect Mixed Linear Model Tools for GWAS |
| Version: | 5.0.1 |
| Date: | 2022-3-27 |
| Maintainer: | Yuan-Ming Zhang <soyzhang@mail.hzau.edu.cn> |
| Contact: | Yuan-Ming Zhang <soyzhang@mail.hzau.edu.cn> |
| Description: | Conduct multi-locus genome-wide association study under the framework of multi-locus random-SNP-effect mixed linear model (mrMLM). First, each marker on the genome is scanned. Bonferroni correction is replaced by a less stringent selection criterion for significant test. Then, all the markers that are potentially associated with the trait are included in a multi-locus genetic model, their effects are estimated by empirical Bayes, and all the nonzero effects were further identified by likelihood ratio test for significant QTL. The program may run on a desktop or laptop computers. If marker genotypes in association mapping population are almost homozygous, these methods in this software are very effective. If there are many heterozygous marker genotypes, the IIIVmrMLM software is recommended. Wen YJ, Zhang H, Ni YL, Huang B, Zhang J, Feng JY, Wang SB, Dunwell JM, Zhang YM, Wu R (2018, <doi:10.1093/bib/bbw145>), and Li M, Zhang YW, Zhang ZC, Xiang Y, Liu MH, Zhou YH, Zuo JF, Zhang HQ, Chen Y, Zhang YM (2022, <doi:10.1016/j.molp.2022.02.012>). |
| Depends: | R (≥ 3.5.0),lars |
| Imports: | Rcpp (≥ 0.12.14),methods,foreach,ncvreg,coin(≥ 1.1-0),sampling,data.table,doParallel,sbl,BEDMatrix |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| LinkingTo: | Rcpp, RcppEigen |
| NeedsCompilation: | yes |
| Packaged: | 2022-03-27 08:03:33 UTC; Administrator |
| Repository: | CRAN |
| Date/Publication: | 2022-03-27 08:50:02 UTC |
| Author: | Ya-Wen Zhang [aut],
Jing-Tian Wang [aut],
Pei Li [aut],
Yuan-Ming Zhang 
[aut, cre] |
process raw data
Description
process raw data for later use
Usage
DoData(genRaw,Genformat,pheRaw1q,kkRaw,psmatrixRaw,covmatrixRaw,trait,
type,PopStrType)
Arguments
genRaw |
raw genotype matrix. |
Genformat |
genotype format. |
pheRaw1q |
raw phenotype matrix. |
kkRaw |
raw kinship matrix. |
psmatrixRaw |
raw population structure matrix. |
covmatrixRaw |
raw covariate matrix. |
trait |
which trait to analysis. |
type |
which type to transform. |
PopStrType |
The type of population structure. |
Author(s)
Zhang Ya-Wen, Wang Jing-Tian, Li Pei, Zhang Yuan-Ming
Maintainer: Yuan-Ming Zhang<soyzhang@mail.hzau.edu.cn>
Examples
G1=data(Gen)
P1=data(Phe)
readraw=ReadData(fileGen=Gen,filePhe=Phe,fileKin=NULL,filePS =NULL,
fileCov=NULL,Genformat=1)
result=DoData(readraw$genRaw,Genformat=1,readraw$pheRaw1q,readraw$kkRaw,
readraw$psmatrixRaw,readraw$covmatrixRaw,trait=1,type=2,PopStrType=NULL)
To perform GWAS with FASTmrEMMA method
Description
FAST multi-locus random-SNP-effect EMMA
Usage
FASTmrEMMA(gen,phe,outATCG,genRaw,kk,psmatrix,svpal,svmlod,Genformat,Likelihood,CLO)
Arguments
gen |
genotype matrix. |
phe |
phenotype matrix. |
outATCG |
genotype for code 1. |
genRaw |
raw genotype. |
kk |
kinship matrix. |
psmatrix |
population structure matrix. |
svpal |
Critical P-value for selecting variable. |
svmlod |
Critical LOD score for significant QTN. |
Genformat |
Format for genotypic codes. |
Likelihood |
restricted maximum likelihood (REML) and maximum likelihood (ML). |
CLO |
number of CPU. |
Author(s)
Zhang Ya-Wen, Wang Jing-Tian, Li Pei, Zhang Yuan-Ming
Maintainer: Yuan-Ming Zhang<soyzhang@mail.hzau.edu.cn>
Examples
G1=data(Gen)
P1=data(Phe)
Readraw=ReadData(fileGen=Gen,filePhe=Phe,fileKin=NULL,filePS =NULL,
Genformat=1)
InputData=inputData(readraw=Readraw,Genformat=1,method="FASTmrEMMA",trait=1)
result=FASTmrEMMA(InputData$doFME$gen,InputData$doFME$phe,
InputData$doFME$outATCG,InputData$doFME$genRaw,
InputData$doFME$kk,InputData$doFME$psmatrix,0.005,
svmlod=3,Genformat=1,Likelihood="REML",CLO=1)
To perform GWAS with FASTmrMLM method
Description
FAST multi-locus random-SNP-effect Mixed Linear Model
Usage
FASTmrMLM(gen,phe,outATCG,genRaw,kk,psmatrix,svpal,svrad,svmlod,Genformat,CLO)
Arguments
gen |
genotype matrix. |
phe |
phenotype matrix. |
outATCG |
genotype for code 1. |
genRaw |
raw genotype. |
kk |
kinship matrix. |
psmatrix |
population structure matrix. |
svpal |
Critical P-value for selecting variable. |
svrad |
Search Radius in search of potentially associated QTN. |
svmlod |
Critical LOD score for significant QTN. |
Genformat |
Format for genotypic codes. |
CLO |
number of CPU. |
Author(s)
Zhang Ya-Wen, Wang Jing-Tian, Li Pei, Zhang Yuan-Ming
Maintainer: Yuan-Ming Zhang<soyzhang@mail.hzau.edu.cn>
Examples
G1=data(Gen)
P1=data(Phe)
Readraw=ReadData(fileGen=Gen,filePhe=Phe,fileKin=NULL,filePS =NULL,
Genformat=1)
InputData=inputData(readraw=Readraw,Genformat=1,method="FASTmrMLM",trait=1)
result=FASTmrMLM(InputData$doMR$gen,InputData$doMR$phe,
InputData$doMR$outATCG,InputData$doMR$genRaw,
InputData$doMR$kk,InputData$doMR$psmatrix,0.01,svrad=20,
svmlod=3,Genformat=1,CLO=1)
Genotype data
Description
Numeric format of genotype dataset.
Usage
data(Gen)
Details
Dataset input of Genotype for mrMLM function.
Author(s)
Maintainer: Yuan-Ming Zhang<soyzhang@mail.hzau.edu.cn>
Genotype of real data
Description
Numeric format of genotype dataset.
Usage
data(Genotype)
Details
Dataset input of Genotype for mrMLM function.
Author(s)
Maintainer: Yuan-Ming Zhang<soyzhang@mail.hzau.edu.cn>
To perform GWAS with ISIS EM-BLASSO method
Description
Iterative Sure Independence Screening EM-Bayesian LASSO
Usage
ISIS(gen,phe,outATCG,genRaw,kk,psmatrix,svpal,svmlod,Genformat,CLO)
Arguments
gen |
genotype matrix. |
phe |
phenotype matrix. |
outATCG |
genotype for code 1. |
genRaw |
raw genotype. |
kk |
kinship matrix. |
psmatrix |
population structure matrix. |
svpal |
Critical P-value for selecting variable. |
svmlod |
Critical LOD score for significant QTN. |
Genformat |
Format for genotypic codes. |
CLO |
number of CPU. |
Author(s)
Zhang Ya-Wen, Li Pei, Zhang Yuan-Ming
Maintainer: Yuan-Ming Zhang<soyzhang@mail.hzau.edu.cn>
Examples
G1=data(Gen)
P1=data(Phe)
Readraw=ReadData(fileGen=Gen,filePhe=Phe,fileKin=NULL,filePS =NULL,
Genformat=1)
InputData=inputData(readraw=Readraw,Genformat=1,method="ISIS EM-BLASSO",
trait=1)
result=ISIS(InputData$doMR$gen,InputData$doMR$phe,InputData$doMR$outATCG,
InputData$doMR$genRaw,InputData$doMR$kk,InputData$doMR$psmatrix,
0.01,svmlod=3,Genformat=1,CLO=1)
Drawing multi-locus Manhattan plot
Description
Using the results of the mrMLM software to draw a multi-locus Manhattan plot
Usage
MultiManhattan(ResultIntermediate,ResultFinal,mar=c(2.9,2.8,0.7,2.8),
LabDistance=1.5,ScaleDistance=0.4,LabelSize=0.8,ScaleSize=0.7,
AxisLwd=5,TckLength=-0.03,LogTimes=2,LODTimes=1.2,lodline=3,
dirplot=getwd(), PlotFormat="tiff",
width=28000,height=7000,pointsize = 60,res=600,
MarkGene=FALSE,Pos_x=NULL,Pos_y=NULL,GeneName=NULL,
GeneNameColour=NULL,...)
Arguments
ResultIntermediate |
Intermediate results obtained by the mrMLM software,"D:/Users/ResultIntermediate.csv". |
ResultFinal |
Final results obtained by the mrMLM software,"D:/Users/ResultFinal.csv". |
mar |
A numerical vector of the form c(bottom, left, top, right) which gives the number of lines of margin to be specified on the four sides of the plot, and the default is c(2.9, 2.8, 0.7, 2.8). |
LabDistance |
Distance between label and axis; the default is 1.5. |
ScaleDistance |
Distance between scale values and axis; the default is 0.4. |
LabelSize |
Size of all the three labels; the default is 0.8. |
ScaleSize |
Size of scale values; the default is 0.7. |
AxisLwd |
The width of axis, a positive number; the default is 5. |
TckLength |
The length of tick marks; the default is -0.03. |
LogTimes |
Magnification of -log10(P-value); the default is 2. |
LODTimes |
Magnification of LOD score; the default is 1.2. |
lodline |
The significant LOD score; the default is 3. |
dirplot |
Path to save plot; the default is current working directory |
PlotFormat |
Format of the plot.i.e., *.tiff, *.png, *.jpeg, *.pdf |
width |
Figure width; the default is 28000. |
height |
Figure height; the default is 7000. |
pointsize |
Word resolution, with the unit of 1/72 inch, being pixels per inch (ppi); the default is 60. |
res |
Figure resolution, with the unit of pixels per inch (ppi); the default is 600. |
MarkGene |
To mark genes in plot or not; if "TRUE" is selected, a file, namely "Reference information to mark gene.csv", that contains the x and y axis information of all the significant QTNs will generate. The default is "FALSE", indicating that no candidate or known gene names are marked in Manhattan plot. |
Pos_x |
Numeric vectors of x axis where the text labels should be written. |
Pos_y |
Numeric vectors of y axis where the text labels should be written. |
GeneName |
A character vector or expression specifying the text to be written. |
GeneNameColour |
The colour of gene names. |
... |
Arguments passed to points, axis, text. |
Author(s)
Zhang Ya-Wen, Wang Jing-Tian, Li Pei, and Zhang Yuan-Ming
Maintainer: Yuan-Ming Zhang<soyzhang@mail.hzau.edu.cn>
Examples
inter<-data(ResultIntermediate)
fin<-data(ResultFinal)
MultiManhattan(ResultIntermediate=ResultIntermediate,ResultFinal=ResultFinal,dirplot=tempdir())
Phenotype dataset
Description
Phenotype dataset of multiple traits.
Usage
data(Phe)
Details
Dataset input of phenotype in mrMLM function.
Author(s)
Maintainer: Yuan-Ming Zhang<soyzhang@mail.hzau.edu.cn>
Phenotype of real data
Description
Phenotype dataset of multiple traits.
Usage
data(Phenotype)
Details
Dataset input of phenotype in mrMLM function.
Author(s)
Maintainer: Yuan-Ming Zhang<soyzhang@mail.hzau.edu.cn>
read raw data
Description
read raw data which have not been transformed
Usage
ReadData(fileGen,filePhe,fileKin,filePS,fileCov,Genformat)
Arguments
fileGen |
genotype matrix. |
filePhe |
phenotype matrix. |
fileKin |
kinship matrix. |
filePS |
population structure matrix. |
fileCov |
Covariate matrix. |
Genformat |
genotype format. |
Author(s)
Zhang Ya-Wen, Wang Jing-Tian, Li Pei, Zhang Yuan-Ming
Maintainer: Yuan-Ming Zhang<soyzhang@mail.hzau.edu.cn>
Examples
G1=data(Gen)
P1=data(Phe)
result=ReadData(fileGen=Gen,filePhe=Phe,fileKin=NULL,filePS =NULL,
fileCov=NULL,Genformat=1)
Final result used to draw manhattan plot.
Description
Final result used to draw manhattan plot.
Usage
data(ResultFinal)
Details
Final result used to draw manhattan plot.
Author(s)
Maintainer: Yuan-Ming Zhang<soyzhang@mail.hzau.edu.cn>
Intermediate result used to draw manhattan plot.
Description
Intermediate result used to draw manhattan plot.
Usage
data(ResultIntermediate)
Details
Intermediate result used to draw manhattan plot.
Author(s)
Maintainer: Yuan-Ming Zhang<soyzhang@mail.hzau.edu.cn>
Input data which have been transformed
Description
Input all the dataset which have been transformed
Usage
inputData(readraw,Genformat,method,trait,PopStrType)
Arguments
readraw |
genotype matrix. |
Genformat |
genotype format. |
method |
which method to analysis. |
trait |
which trait to analysis. |
PopStrType |
The type of population structure. |
Author(s)
Zhang Ya-Wen, Wang Jing-Tian, Li Pei, Zhang Yuan-Ming
Maintainer: Yuan-Ming Zhang<soyzhang@mail.hzau.edu.cn>
Examples
G1=data(Gen)
P1=data(Phe)
Readraw=ReadData(fileGen=Gen,filePhe=Phe,fileKin=NULL,filePS =NULL,
fileCov=NULL,Genformat=1)
result=inputData(readraw=Readraw,Genformat=1,method="mrMLM",trait=1,
PopStrType=NULL)
Multi-Locus Random-SNP-Effect Mixed Linear Model Tools for GWAS
Description
Conduct multi-locus genome-wide association study under the framework of multi-locus random-SNP-effect mixed linear model (mrMLM). First, each marker on the genome is scanned. Bonferroni correction is replaced by a less stringent selection criterion for significant test. Then, all the markers that are potentially associated with the trait are included in a multi-locus genetic model, their effects are estimated by empirical Bayes, and all the nonzero effects were further identified by likelihood ratio test for true QTL. The program may run on a desktop or laptop computers. If marker genotypes in association mapping population are almost homozygous, these methods in this software are very effective. If there are many heterozygous marker genotypes, the IIIVmrMLM software is recommended. Wen YJ, Zhang H, Ni YL, Huang B, Zhang J, Feng JY, Wang SB, Dunwell JM, Zhang YM, Wu R (2018, <doi:10.1093/bib/bbw145>), and Li M, Zhang YW, Zhang ZC, Xiang Y, Liu MH, Zhou YH, Zuo JF, Zhang HQ, Chen Y, Zhang YM (2022, <doi:10.1016/j.molp.2022.02.012>).
Usage
mrMLM(fileGen,filePhe,fileKin,filePS,PopStrType,fileCov,Genformat,
method,Likelihood,trait,SearchRadius,CriLOD,SelectVariable,Bootstrap,
DrawPlot,Plotformat,dir,PC,RAM)
Arguments
fileGen |
File path and name in your computer of Genotype, i.e.,"D:/Users/Genotype_num.csv". |
filePhe |
File path and name in your computer of Phenotype, i.e.,"D:/Users/Phenotype.csv". |
fileKin |
File path and name in your computer of Kinship, i.e.,"D:/Users/Kinship.csv". |
filePS |
File path and name in your computer of Population Structure,i.e.,"D:/Users/PopStr.csv". |
PopStrType |
The type of population structure,i.e.,Q (Q matrix), PCA (principal components), EvolPopStr (evolutionary population structure). |
fileCov |
File path and name in your computer of covariate, i.e.,"D:/Users/Covariate.csv". |
Genformat |
Format for genotypic codes, Num (number), Cha (character) and Hmp (Hapmap). |
method |
Six multi-locus GWAS methods. Users may select one to six methods, including mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB and ISIS EM-BLASSO. |
Likelihood |
This parameter is only for FASTmrEMMA, including REML(restricted maximum likelihood) and ML(maximum likelihood). |
trait |
Traits analyzed from number 1 to number 2,i.e.,1:2. |
SearchRadius |
This parameter is only for mrMLM and FASTmrMLM, indicating Search Radius in search of potentially associated QTN,the default is 20. |
CriLOD |
Critical LOD score for significant QTN. |
SelectVariable |
This parameter is only for pLARmEB. SelectVariable=50 indicates that 50 potentially associated variables are selected from each chromosome. Users may change this number in real data analysis in order to obtain the best results as final results,the default is 50. |
Bootstrap |
This parameter is only for pLARmEB, including FASLE and TRUE, Bootstrap=FALSE indicates the analysis of only real dataset, Bootstrap=TRUE indicates the analysis of both real dataset and four resampling datasets,the default is FALSE. |
DrawPlot |
This parameter is for all the six methods, including FALSE and TRUE, DrawPlot=FALSE indicates no figure output, DrawPlot=TRUE indicates the output of the Manhattan, QQ figures,the default is TRUE. |
Plotformat |
This parameter is for all the figure files, including *.jpeg, *.png, *.tiff and *.pdf,the default is "tiff". |
dir |
This parameter is for the save path,i.e.,"D:/Users" |
PC |
This parameter is used to specify whether only small RAM device is available to run the mrMLM program, such as desktop or laptop. The default value is PC=FALSE. PC=TRUE indicates running the program on low RAM desktop or laptop. |
RAM |
This parameter is the RAM of your desktop or laptop. The default value is RAM=4. RAM=4 indicates the RAM of your device is 4G. |
Details
| Package: | mrMLM |
| Type: | Package |
| Version: | 5.0.1 |
| Date: | 2022-3-27 |
| Depends: | lars |
| Imports: | methods,foreach,ncvreg,coin,sampling,data.table,doParallel,BEDMatrix |
| License: | GPL version 2 or newer |
| LazyLoad: | yes |
Note
Once the running of the software mrMLM v5.0.1 is ended, the "results" files should appear on the Directory, which was set up by users before running the software. The results for each trait include "*_intermediate result.csv", "*_Final result.csv", Manhattan plot, and QQ plot. If only pLARmEB and ISIS EM-BLASSO methods are selected, there will be no intermediate results and figures output. Users can decompress the mrMLM package and find the User Manual file (name: Instruction.pdf) in the folder of ".../mrMLM/inst".
Author(s)
Zhang Ya-Wen, Wang Jing-Tian, Li Pei, Zhang Yuan-Ming
Maintainer: Yuan-Ming Zhang<soyzhang@mail.hzau.edu.cn>
References
1. Zhang YM, Mao Y, Xie C, Smith H, Luo L, Xu S. Genetics 2005,169:2267-2275. 2. Wang SB, Feng JY, Ren WL, Huang B, Zhou L, Wen YJ, Zhang J, Dunwell JM, Xu S, Zhang YM. Sci Rep 2016,6:19444. 3. Tamba CL, Ni YL, Zhang YM. PLoS Comput Biol 2017,13(1):e1005357. 4. Zhang J, Feng JY, Ni YL, Wen YJ, Niu Y, Tamba CL, Yue C, Song Q, Zhang YM. Heredity 2018,118(6):517-524. 5. Ren WL, Wen YJ, Dunwell JM, Zhang YM. Heredity 2018,120(3): 208-218. 6. Wen YJ, Zhang H, Ni YL, Huang B, Zhang J, Feng JY, Wang SB, Dunwell JM, Zhang YM, Wu R. Brief Bioinform 2018,19(4): 700-712. 7. Tamba CL, Zhang YM. bioRxiv,preprint first posted online Jun. 7, 2018, doi:https://doi.org/10.1101/341784. 8. Zhang YW, Tamba CL, Wen YJ, Li P, Ren WL, Ni YL, Gao J, Zhang YM. Genomics, Proteomics & Bioinformatics 2020, 18: 481-487. 9.Li M, Zhang YW, Zhang ZC, Xiang Y, Liu MH, Zhou YH, Zuo JF, Zhang HQ, Chen Y, Zhang YM. A compressed variance component mixed model for detecting QTNs, and QTN-by-environment and QTN-by-QTN interactions in genome-wide association studies. Molecular Plant 2022, online, S1674-2052(22)00060-0. doi: 10.1016/j.molp.2022.02.012.
Examples
Ge1=data(Genotype)
Ph1=data(Phenotype)
mrMLM(fileGen=Genotype,filePhe=Phenotype,Genformat="Num",
method=c("FASTmrMLM"),trait=1,CriLOD=3,DrawPlot=FALSE,
dir=tempdir(),PC=FALSE,RAM=4)
To perform GWAS with mrMLM method
Description
multi-locus random-SNP-effect Mixed Linear Model
Usage
mrMLMFun(gen,phe,outATCG,genRaw,kk,psmatrix,svpal,svrad,svmlod,Genformat,CLO)
Arguments
gen |
genotype matrix. |
phe |
phenotype matrix. |
outATCG |
genotype for code 1. |
genRaw |
raw genotype. |
kk |
kinship matrix. |
psmatrix |
population structure matrix. |
svpal |
Critical P-value for selecting variable |
svrad |
Search Radius in search of potentially associated QTN. |
svmlod |
Critical LOD score for significant QTN. |
Genformat |
Format for genotypic codes. |
CLO |
number of CPU. |
Author(s)
Zhang Ya-Wen, Wang Jing-Tian, Li Pei, Zhang Yuan-Ming
Maintainer: Yuan-Ming Zhang<soyzhang@mail.hzau.edu.cn>
Examples
G1=data(Gen)
P1=data(Phe)
Readraw=ReadData(fileGen=Gen,filePhe=Phe,fileKin=NULL,filePS =NULL,
Genformat=1)
InputData=inputData(readraw=Readraw,Genformat=1,method="mrMLM",trait=1)
result=mrMLMFun(InputData$doMR$gen,InputData$doMR$phe,InputData$doMR$outATCG,
InputData$doMR$genRaw,InputData$doMR$kk,InputData$doMR$psmatrix,
0.01,svrad=20,svmlod=3,Genformat=1,CLO=1)
Matrix multiplication acceleration algorithm.
Description
Matrix multiplication acceleration algorithm.
Usage
multiplication_speed(A,B)
Arguments
A |
matrix A. |
B |
matrix B. |
Author(s)
Zhang Ya-Wen, Wen Yang-Jun, Wang Shi-Bo, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<soyzhang@mail.hzau.edu.cn>
Examples
## Not run:
A<-matrix(1:10,2,5)
B<-matrix(1:10,5:2)
result<-multiplication_speed(A,B)
## End(Not run)
To perform GWAS with pKWmEB method
Description
Kruskal-Wallis test with empirical Bayes under polygenic background control
Usage
pKWmEB(gen,phe,outATCG,genRaw,kk,psmatrix,svpal,svmlod,Genformat,CLO)
Arguments
gen |
genotype matrix. |
phe |
phenotype matrix. |
outATCG |
genotype for code 1. |
genRaw |
raw genotype. |
kk |
kinship matrix. |
psmatrix |
population structure matrix. |
svpal |
Critical P-value for selecting variable. |
svmlod |
Critical LOD score for significant QTN. |
Genformat |
Format for genotypic codes. |
CLO |
number of CPU. |
Author(s)
Zhang Ya-Wen, Wang Jing-Tian, Li Pei, Zhang Yuan-Ming
Maintainer: Yuan-Ming Zhang<soyzhang@mail.hzau.edu.cn>
Examples
G1=data(Gen)
P1=data(Phe)
Readraw=ReadData(fileGen=Gen,filePhe=Phe,fileKin=NULL,filePS =NULL,
Genformat=1)
InputData=inputData(readraw=Readraw,Genformat=1,method="pKWmEB",trait=1)
result=pKWmEB(InputData$doMR$gen,InputData$doMR$phe,InputData$doMR$outATCG,
InputData$doMR$genRaw,InputData$doMR$kk,InputData$doMR$psmatrix,
0.05,svmlod=3,Genformat=1,CLO=1)
To perform GWAS with pLARmEB method
Description
polygene-background-control-based least angle regression plus Empirical Bayes
Usage
pLARmEB(gen,phe,outATCG,genRaw,kk,psmatrix,CriLOD,lars1,Genformat,Bootstrap,CLO)
Arguments
gen |
genotype matrix. |
phe |
phenotype matrix. |
outATCG |
genotype for code 1. |
genRaw |
raw genotype. |
kk |
kinship matrix. |
psmatrix |
population structure matrix. |
CriLOD |
Critical LOD score for significant QTN. |
lars1 |
No. of potentially associated variables selected by LARS. |
Genformat |
Format for genotypic codes. |
Bootstrap |
Bootstrap=FALSE indicates the analysis of only real dataset, Bootstrap=TRUE indicates the analysis of both real dataset and four resampling datasets. |
CLO |
number of CPU. |
Author(s)
Zhang Ya-Wen, Wang Jing-Tian, Li Pei, Zhang Yuan-Ming
Maintainer: Yuan-Ming Zhang<soyzhang@mail.hzau.edu.cn>
Examples
G1=data(Gen)
P1=data(Phe)
Readraw=ReadData(fileGen=Gen,filePhe=Phe,fileKin=NULL,filePS =NULL,
Genformat=1)
InputData=inputData(readraw=Readraw,Genformat=1,method="pLARmEB",trait=1)
result=pLARmEB(InputData$doMR$gen,InputData$doMR$phe,InputData$doMR$outATCG,
InputData$doMR$genRaw,InputData$doMR$kk,InputData$doMR$psmatrix,
CriLOD=3,lars1=20,Genformat=1,Bootstrap=FALSE,CLO=1)