| Title: | Segregation Analysis |
|---|---|
| Description: | A few major genes and a series of polygene are responsive for each quantitative trait. Major genes are individually identified while polygene is collectively detected. This is mixed major genes plus polygene inheritance analysis or segregation analysis (SEA). In the SEA, phenotypes from a single or multiple bi-parental segregation populations along with their parents are used to fit all the possible models and the best model of the trait for population phenotypic distributions is viewed as the model of the trait. There are fourteen types of population combinations available. Zhang Yuan-Ming, Gai Jun-Yi, Yang Yong-Hua (2003, <doi:10.1017/S0016672303006141>). |
| Authors: | Jing-Tian Wang [aut], Ya-Wen Zhang [aut], Yuan-Ming Zhang [aut,
cre] |
| Maintainer: | Yuan-Ming Zhang <[email protected]> |
| License: | GPL (>= 2) |
| Version: | 2.0.1 |
| Built: | 2024-10-31 20:28:05 UTC |
| Source: | https://github.com/cran/SEA |
A few major genes and a series of polygene are responsive for each quantitative trait. Major genes are individually identified while polygene is collectively detected. This is mixed major genes plus polygene inheritance analysis or segregation analysis (SEA). In the SEA, phenotypes from a single or multiple bi-parental segregation populations along with their parents are used to fit all the possible models and the best model for population phenotypic distributions is viewed as the model of the trait. There are fourteen types of population combinations available. Zhang Yuan-Ming, Gai Jun-Yi, Yang Yong-Hua (2003, <doi:10.1017/S0016672303006141>), and Wang Jing-Tian, Zhang Ya-Wen, Du Ying-Wen, Ren Wen-Long, Li Hong-Fu, Sun Wen-Xian, Ge Chao, and Zhang Yuan-Ming(2022, <doi:10.3724/SP.J.1006.2022.14088>)
| Package: | SEA |
| Type: | Package |
| Version: | 2.0.1 |
| Date: | 2022-03-28 |
| Depends: | shiny,MASS,doParallel,foreach |
| Imports: | KScorrect,kolmim,utils,stats,grDevices,graphics,data.table |
| License: | GPL(>=2) |
| LazyLoad: | yes |
Users can use 'SEA()' start the GUI.
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
The EIM algorithm in the joint segregation analysis of quantitative traits. Zhang Yuan-Ming*,Gai Junyi,Yang Yonghua(2003).
## Not run: SEA()## Not run: SEA()
The phenotype of BC population .
data(BCexdata)data(BCexdata)
Dataset input of BCFun function.
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
The phenotype of BCF population .
data(BCFexdata)data(BCFexdata)
Dataset input of BCFFun function.
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
Phenotypic observations in BCF population have often been used to identify mixed major-gene plus polygene inheritance model for quantitative traits in plants.
BCFFun(df,model,BCFtext2)BCFFun(df,model,BCFtext2)
df |
phenotype matrix. |
model |
genetic model. |
BCFtext2 |
number of plants measured in each family. |
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
BCF=data(BCFexdata) BCFFun(BCFexdata,"0MG",1)BCF=data(BCFexdata) BCFFun(BCFexdata,"0MG",1)
Phenotypic observations in BC population have often been used to identify mixed major-gene plus polygene inheritance model for quantitative traits in plants.
BCFun(df,model)BCFun(df,model)
df |
phenotype matrix. |
model |
genetic model. |
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
BC=data(BCexdata) BCFun(BCexdata,"0MG")BC=data(BCexdata) BCFun(BCexdata,"0MG")
The phenotype of BIL population .
data(BILexdata)data(BILexdata)
Dataset input of BILFun function.
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
Phenotypic observations in BIL population have often been used to identify mixed major-gene plus polygene inheritance model for quantitative traits in plants.
BILFun(df,model,BILfr)BILFun(df,model,BILfr)
df |
phenotype matrix. |
model |
genetic model. |
BILfr |
BIL type. |
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
BIL=data(BILexdata) BILFun(BILexdata,"0MG","BIL1(F1xP1)")BIL=data(BILexdata) BILFun(BILexdata,"0MG","BIL1(F1xP1)")
The phenotype of DH population .
data(DHexdata)data(DHexdata)
Dataset input of DHFun function.
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
Phenotypic observations in DH population have often been used to identify mixed major-gene plus polygene inheritance model for quantitative traits in plants.
DHFun(df,model)DHFun(df,model)
df |
phenotype matrix. |
model |
genetic model. |
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
DH=data(DHexdata) DHFun(DHexdata,"0MG")DH=data(DHexdata) DHFun(DHexdata,"0MG")
The phenotype of F23 population .
data(F23exdata)data(F23exdata)
Dataset input of F23Fun function.
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
Phenotypic observations in F23 population have often been used to identify mixed major-gene plus polygene inheritance model for quantitative traits in plants.
F23Fun(df,model,m_nf)F23Fun(df,model,m_nf)
df |
phenotype matrix. |
model |
genetic model. |
m_nf |
number of plants measured in each family. |
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
F23=data(F23exdata) F23Fun(F23exdata,"0MG",1)F23=data(F23exdata) F23Fun(F23exdata,"0MG",1)
The phenotype of F2 population .
data(F2exdata)data(F2exdata)
Dataset input of F2Fun function.
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
Phenotypic observations in F2 population have often been used to identify mixed major-gene plus polygene inheritance model for quantitative traits in plants.
F2Fun(df,model)F2Fun(df,model)
df |
phenotype matrix. |
model |
genetic model. |
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
F2=data(F2exdata) F2Fun(F2exdata,"0MG")F2=data(F2exdata) F2Fun(F2exdata,"0MG")
The phenotype of G3DH population .
data(G3DHexdata)data(G3DHexdata)
Dataset input of G3DHFun function.
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
Phenotypic observations in G3DH population have often been used to identify mixed major-gene plus polygene inheritance model for quantitative traits in plants.
G3DHFun(df,model,G3DHtext2)G3DHFun(df,model,G3DHtext2)
df |
phenotype matrix. |
model |
genetic model. |
G3DHtext2 |
number of plants measured in each family. |
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
G3DH=data(G3DHexdata) G3DHFun(G3DHexdata,"0MG",1)G3DH=data(G3DHexdata) G3DHFun(G3DHexdata,"0MG",1)
The phenotype of G4F2 population .
data(G4F2exdata)data(G4F2exdata)
Dataset input of G4F2Fun function.
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
Phenotypic observations in G4F2 population have often been used to identify mixed major-gene plus polygene inheritance model for quantitative traits in plants.
G4F2Fun(df,model)G4F2Fun(df,model)
df |
phenotype matrix. |
model |
genetic model. |
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
G4F2=data(G4F2exdata) G4F2Fun(G4F2exdata,"PG-AD")G4F2=data(G4F2exdata) G4F2Fun(G4F2exdata,"PG-AD")
The phenotype of G4F3 population .
data(G4F3exdata)data(G4F3exdata)
Dataset input of G4F3Fun function.
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
Phenotypic observations in G4F3 population have often been used to identify mixed major-gene plus polygene inheritance model for quantitative traits in plants.
G4F3Fun(df,model,G4F3text2)G4F3Fun(df,model,G4F3text2)
df |
phenotype matrix. |
model |
genetic model. |
G4F3text2 |
number of plants measured in each family. |
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
G4F3=data(G4F3exdata) G4F3Fun(G4F3exdata,"PG-AD",1)G4F3=data(G4F3exdata) G4F3Fun(G4F3exdata,"PG-AD",1)
The phenotype of G5BC population .
data(G5BCexdata)data(G5BCexdata)
Dataset input of G5BCFun function.
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
The phenotype of G5BCF population .
data(G5BCFexdata)data(G5BCFexdata)
Dataset input of G5BCFFun function.
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
Phenotypic observations in G5BCF population have often been used to identify mixed major-gene plus polygene inheritance model for quantitative traits in plants.
G5BCFFun(df,model,G5BCFtext2)G5BCFFun(df,model,G5BCFtext2)
df |
phenotype matrix. |
model |
genetic model. |
G5BCFtext2 |
number of plants measured in each family. |
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
G5BCF=data(G5BCFexdata) G5BCFFun(G5BCFexdata,"1MG-AD",1)G5BCF=data(G5BCFexdata) G5BCFFun(G5BCFexdata,"1MG-AD",1)
Phenotypic observations in G5BC population have often been used to identify mixed major-gene plus polygene inheritance model for quantitative traits in plants.
G5BCFun(df,model)G5BCFun(df,model)
df |
phenotype matrix. |
model |
genetic model. |
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
G5BC=data(G5BCexdata) G5BCFun(G5BCexdata,"1MG-AD")G5BC=data(G5BCexdata) G5BCFun(G5BCexdata,"1MG-AD")
The phenotype of G5 population .
data(G5exdata)data(G5exdata)
Dataset input of G5Fun function.
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
Phenotypic observations in G5 population have often been used to identify mixed major-gene plus polygene inheritance model for quantitative traits in plants.
G5Fun(df,model,G5text2)G5Fun(df,model,G5text2)
df |
phenotype matrix. |
model |
genetic model. |
G5text2 |
number of plants measured in each family. |
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
G5=data(G5exdata) G5Fun(G5exdata,"PG-AD",1)G5=data(G5exdata) G5Fun(G5exdata,"PG-AD",1)
The phenotype of G6 population .
data(G6exdata)data(G6exdata)
Dataset input of G6Fun function.
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
The phenotype of G6F population .
data(G6Fexdata)data(G6Fexdata)
Dataset input of G6FFun function.
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
Phenotypic observations in G6F population have often been used to identify mixed major-gene plus polygene inheritance model for quantitative traits in plants.
G6FFun(df,model,G6Ftext2)G6FFun(df,model,G6Ftext2)
df |
phenotype matrix. |
model |
genetic model. |
G6Ftext2 |
number of plants measured in each family. |
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
G6F=data(G6Fexdata) G6FFun(G6Fexdata,"PG-AD",1)G6F=data(G6Fexdata) G6FFun(G6Fexdata,"PG-AD",1)
Phenotypic observations in G6 population have often been used to identify mixed major-gene plus polygene inheritance model for quantitative traits in plants.
G6Fun(df,model)G6Fun(df,model)
df |
phenotype matrix. |
model |
genetic model. |
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
G6=data(G6exdata) G6Fun(G6exdata,"PG-AD")G6=data(G6exdata) G6Fun(G6exdata,"PG-AD")
calculate posterior probability of the optimal model
PosPro(Population,result,data)PosPro(Population,result,data)
Population |
which Population to analysis. |
result |
result of calculation used corresponding population function. |
data |
phenotype matrix. |
Wang Jing-Tian, Zhang Ya-Wen, and Zhang Yuan-Ming
Maintainer: Yuanming Zhang<[email protected]>
F23=data(F23exdata) result<-F23Fun(F23exdata,"1MG-AD",1) PosPro("F2:3",result,F23exdata)F23=data(F23exdata) result<-F23Fun(F23exdata,"1MG-AD",1) PosPro("F2:3",result,F23exdata)