DiallelAnalysisR (version 0.6.0)

Griffing: Diallel Analysis using Griffing Approach

Description

Griffing is used for performing Diallel Analysis using Griffing's Approach.

Usage

Griffing(y, Rep, Cross1, Cross2, data, Method, Model)

Value

Means Means

ANOVA Analysis of Variance (ANOVA) table

Genetic.Components Genetic Components

Effects Effects of Crosses

StdErr Standard Errors of Crosses

Arguments

y

Numeric Response Vector

Rep

Replicate as factor

Cross1

Cross 1 as factor

Cross2

Cross 2 as factor

data

A data.frame

Method

Method for Diallel Analysis using Griffing's approach. It can take 1, 2, 3, or 4 as argument depending on the method being used.

1. Method-I (Parents + \(F_{1}\)'s + reciprocals);

2. Method-II (Parents and one set of \(F_{1}\)'s);

3. Method-III (One set of \(F_{1}\)'s and reciprocals);

4. Method-IV (One set of \(F_{1}\)'s only).

Model

Model for Diallel Analysis using Griffing's approach. It can take 1 or 2 as arguments depending on the model being used.

1. Fixed Effects Model;

2. Random Effects Model.

Author

Muhammad Yaseen ()

Details

Diallel Analysis using Griffing's approach.

References

1. Griffing, B. (1956) Concept of General and Specific Combining Ability in relation to Diallel Crossing Systems. Australian Journal of Biological Sciences, 9(4), 463--493.

2. Singh, R. K. and Chaudhary, B. D. (2004) Biometrical Methods in Quantitative Genetic Analysis. New Delhi: Kalyani.

See Also

Hayman , GriffingData1 , GriffingData2 , GriffingData3 , GriffingData4

Examples

#-------------------------------------------------------------
## Diallel Analysis with Griffing's Aproach Method 1 & Model 1
#-------------------------------------------------------------
Griffing1Data1 <-
 Griffing(
     y      = Yield
   , Rep    = Rep
   , Cross1 = Cross1
   , Cross2 = Cross2
   , data   = GriffingData1
   , Method = 1
   , Model  = 1
 )
names(Griffing1Data1)
Griffing1Data1
Griffing1Data1Means <- Griffing1Data1$Means
Griffing1Data1ANOVA <- Griffing1Data1$ANOVA
Griffing1Data1Genetic.Components <- Griffing1Data1$Genetic.Components
Griffing1Data1Effects <- Griffing1Data1$Effects
Griffing1Data1StdErr <- as.matrix(Griffing1Data1$StdErr)


#--------------------------------------------------------------
## Diallel Analysis with Griffing's Aproach Method 1 & Model 2
#--------------------------------------------------------------
Griffing2Data1 <-
 Griffing(
     y      = Yield
   , Rep    = Rep
   , Cross1 = Cross1
   , Cross2 = Cross2
   , data   = GriffingData1
   , Method = 1
   , Model  = 2
 )
names(Griffing2Data1)
Griffing2Data1
Griffing2Data1Means <- Griffing2Data1$Means
Griffing2Data1ANOVA <- Griffing2Data1$ANOVA
Griffing2Data1Genetic.Components <- Griffing2Data1$Genetic.Components


#--------------------------------------------------------------
## Diallel Analysis with Griffing's Aproach Method 2 & Model 1
#--------------------------------------------------------------
Griffing1Data2 <-
 Griffing(
     y      = Yield
   , Rep    = Rep
   , Cross1 = Cross1
   , Cross2 = Cross2
   , data   = GriffingData2
   , Method = 2
   , Model  = 1
 )
names(Griffing1Data2)
Griffing1Data2
Griffing1Data2Means <- Griffing1Data2$Means
Griffing1Data2ANOVA <- Griffing1Data2$ANOVA
Griffing1Data2Genetic.Components <- Griffing1Data2$Genetic.Components
Griffing1Data2Effects <- Griffing1Data2$Effects
Griffing1Data2StdErr <- as.matrix(Griffing1Data2$StdErr)


#--------------------------------------------------------------
## Diallel Analysis with Griffing's Aproach Method 2 & Model 2
#--------------------------------------------------------------
Griffing2Data2 <-
 Griffing(
     y      = Yield
   , Rep    = Rep
   , Cross1 = Cross1
   , Cross2 = Cross2
   , data   = GriffingData2
   , Method = 2
   , Model  = 2
 )
names(Griffing2Data2)
Griffing2Data2
Griffing2Data2Means <- Griffing2Data2$Means
Griffing2Data2ANOVA <- Griffing2Data2$ANOVA
Griffing2Data2Genetic.Components <- Griffing2Data2$Genetic.Components


#--------------------------------------------------------------
## Diallel Analysis with Griffing's Aproach Method 3 & Model 1
#--------------------------------------------------------------
Griffing1Data3 <-
 Griffing(
     y      = Yield
   , Rep    = Rep
   , Cross1 = Cross1
   , Cross2 = Cross2
   , data   = GriffingData3
   , Method = 3
   , Model  = 1
 )
names(Griffing1Data3)
Griffing1Data3
Griffing1Data3Means <- Griffing1Data3$Means
Griffing1Data3ANOVA <- Griffing1Data3$ANOVA
Griffing1Data3Genetic.Components <- Griffing1Data3$Genetic.Components
Griffing1Data3Effects <- Griffing1Data3$Effects
Griffing1Data3StdErr <- as.matrix(Griffing1Data3$StdErr)


#--------------------------------------------------------------
## Diallel Analysis with Griffing's Aproach Method 3 & Model 2
#--------------------------------------------------------------
Griffing2Data3 <-
 Griffing(
     y       = Yield
   , Rep     = Rep
   , Cross1  = Cross1
   , Cross2  = Cross2
   , data    = GriffingData3
   , Method  = 3
   , Model   = 2
 )
names(Griffing2Data3)
Griffing2Data3
Griffing2Data3Means <- Griffing2Data3$Means
Griffing2Data3ANOVA <- Griffing2Data3$ANOVA
Griffing2Data3Genetic.Components <- Griffing2Data3$Genetic.Components


#--------------------------------------------------------------
## Diallel Analysis with Griffing's Aproach Method 4 & Model 1
#--------------------------------------------------------------
Griffing1Data4 <-
 Griffing(
     y       = Yield
   , Rep     = Rep
   , Cross1  = Cross1
   , Cross2  = Cross2
   , data    = GriffingData4
   , Method  = 4
   , Model   = 1
 )
names(Griffing1Data4)
Griffing1Data4
Griffing1Data4Means <- Griffing1Data4$Means
Griffing1Data4ANOVA <- Griffing1Data4$ANOVA
Griffing1Data4Genetic.Components <- Griffing1Data4$Genetic.Components
Griffing1Data4Effects <- Griffing1Data4$Effects
Griffing1Data4StdErr <- as.matrix(Griffing1Data4$StdErr)


#--------------------------------------------------------------
## Diallel Analysis with Griffing's Aproach Method 4 & Model 2
#--------------------------------------------------------------
Griffing2Data4 <-
 Griffing(
     y       = Yield
   , Rep     = Rep
   , Cross1  = Cross1
   , Cross2  = Cross2
   , data    = GriffingData4
   , Method  = 4
   , Model   = 2
 )
names(Griffing2Data4)
Griffing2Data4
Griffing2Data4Means <- Griffing2Data4$Means
Griffing2Data4ANOVA <- Griffing2Data4$ANOVA
Griffing2Data4Genetic.Components <- Griffing2Data4$Genetic.Components