Package 'DiallelAnalysisR'

Title: Diallel Analysis with R
Description: Performs Diallel Analysis with R using Griffing's and Hayman's approaches. Four different Methods (1: Method-I (Parents + F1's + reciprocals); 2: Method-II (Parents and one set of F1's); 3: Method-III (One set of F1's and reciprocals); 4: Method-IV (One set of F1's only)) and two Models (1: Fixed Effects Model; 2: Random Effects Model) can be applied using Griffing's approach.
Authors: Muhammad Yaseen [aut, cre, cph] , Kent Eskridge [ctb, aut], Pedro Barbosa [ctb, aut], Yuhang Guo [ctb, aut]
Maintainer: Muhammad Yaseen <[email protected]>
License: GPL-2 | GPL-3
Version: 0.6.0
Built: 2024-11-12 06:12:14 UTC
Source: https://github.com/myaseen208/diallelanalysisr

Help Index

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)

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 + F1F_{1}'s + reciprocals);

  2. Method-II (Parents and one set of F1F_{1}'s);

  3. Method-III (One set of F1F_{1}'s and reciprocals);

  4. Method-IV (One set of F1F_{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.

Details

Diallel Analysis using Griffing's approach.

Value

Means Means

ANOVA Analysis of Variance (ANOVA) table

Genetic.Components Genetic Components

Effects Effects of Crosses

StdErr Standard Errors of Crosses

Author(s)

Muhammad Yaseen ([email protected])

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

Data for Diallel Analysis using Griffing Approach Method 1

Description

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

Usage

data(GriffingData1)

Format

A data.frame with 256 rows and 4 variables.

Details

  • Cross1 Cross 1

  • Cross2 Cross 2

  • Rep Replicate

  • Yield Yield Response

Author(s)

Muhammad Yaseen ([email protected])

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

Griffing , GriffingData2 , GriffingData3 , GriffingData4

Examples

data(GriffingData1)

Data for Diallel Analysis using Griffing Approach Method 2

Description

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

Usage

data(GriffingData2)

Format

A data.frame with 144 rows and 4 variables.

Details

  • Cross1 Cross 1

  • Cross2 Cross 2

  • Rep Replicate

  • Yield Yield Response

Author(s)

Muhammad Yaseen ([email protected])

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

Griffing , GriffingData1 , GriffingData3 , GriffingData4

Examples

data(GriffingData2)

Data for Diallel Analysis using Griffing Approach Method 3

Description

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

Usage

data(GriffingData3)

Format

A data.frame with 224 rows and 4 variables.

Details

  • Cross1 Cross 1

  • Cross2 Cross 2

  • Rep Replicate

  • Yield Yield Response

Author(s)

Muhammad Yaseen ([email protected])

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

Griffing , GriffingData1 , GriffingData2 , GriffingData4

Examples

data(GriffingData3)

Data for Diallel Analysis using Griffing Approach Method 4

Description

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

Usage

data(GriffingData4)

Format

A data.frame with 112 rows and 4 variables.

Details

  • Cross1 Cross 1

  • Cross2 Cross 2

  • Rep Replicate

  • Yield Yield Response

Author(s)

Muhammad Yaseen ([email protected])

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

Griffing , GriffingData1 , GriffingData2 , GriffingData3

Examples

data(GriffingData4)

Diallel Analysis using Hayman Approach

Description

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

Usage

Hayman(y, Rep, Cross1, Cross2, data)

Arguments

y

Numeric Response Vector
Rep

Replicate as factor
Cross1

Cross 1 as factor
Cross2

Cross 2 as factor
data

A data.frame

Details

Diallel Analysis using Haymans's approach.

Value

Means Means

ANOVA Analysis of Variance (ANOVA) table

Genetic.Components Genetic Components

Effects Effects of Crosses

StdErr Standard Errors of Crosses

Author(s)

Muhammad Yaseen ([email protected])

References

  1. Hayman, B. I. (1954 a) The Theory and Analysis of Diallel Crosses. Genetics, 39, 789–809.

  2. Hayman, B. I. (1954 b) The Analysis of Variance of Diallel Tables. Biometrics, 10, 235–244.

  3. Hayman, B. I. (1957) Interaction, Heterosis and Diallel Crosses. Genetics, 42, 336–355.

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

See Also

Griffing , HaymanData

Examples

#------------------------------------------
## Diallel Analysis with Haymans's Aproach
#------------------------------------------

Hayman1Data <-
 Hayman(
     y      = Yield
   , Rep    = Rep
   , Cross1 = Cross1
   , Cross2 = Cross2
   , data   = HaymanData
   )

Hayman1Data
names(Hayman1Data)

Hayman1DataMeans <- Hayman1Data$Means
Hayman1DataANOVA <- Hayman1Data$ANOVA
Hayman1DataWr.Vr.Table <- Hayman1Data$Wr.Vr.Table

Hayman1DataComponents.of.Variation <- Hayman1Data$Components.of.Variation
Hayman1DataOther.Parameters <- Hayman1Data$Other.Parameters
Hayman1DataFr <- Hayman1Data$Fr

#----------------
# Wr-Vr Graph
#----------------
VOLO     <- Hayman1Data$VOLO
In.Value <- Hayman1Data$In.Value
a        <- Hayman1Data$a
b        <- Hayman1Data$b
Wr.Vr    <- Hayman1Data$Wr.Vr.Table


library(ggplot2)
ggplot(data=data.frame(x=c(0, max(In.Value, Wr.Vr$Vr, Wr.Vr$Wr, Wr.Vr$Wrei))), aes(x)) +
  stat_function(fun=function(x) {sqrt(x*VOLO)}, color="blue") +
  geom_hline(yintercept = 0) +
  geom_vline(xintercept = 0) +
  geom_abline(intercept = a, slope = b) +
  geom_abline(intercept = mean(Wr.Vr$Wr)-mean(Wr.Vr$Vr), slope = 1) +
  geom_segment(aes(
      x     = mean(Wr.Vr$Vr)
    , y     = min(0, mean(Wr.Vr$Wr))
    , xend  = mean(Wr.Vr$Vr)
    , yend  = max(0, mean(Wr.Vr$Wr))
  )
  , color = "green"
  ) +
  geom_segment(aes(
      x     = min(0, mean(Wr.Vr$Vr))
    , y     = mean(Wr.Vr$Wr)
    , xend  = max(0, mean(Wr.Vr$Vr))
    , yend  = mean(Wr.Vr$Wr)
  )
  , color = "green"
  )  +
  lims(x=c(min(0, Wr.Vr$Vr, Wr.Vr$Wrei), max(Wr.Vr$Vr, Wr.Vr$Wrei)),
       y=c(min(0, Wr.Vr$Wr, Wr.Vr$Wrei), max(Wr.Vr$Wr, Wr.Vr$Wri))
  ) +
  labs(
         x = expression(V[r])
       , y = expression(W[r])
       , title = expression(paste(W[r]-V[r] , " Graph"))
       ) +
  theme_bw()

Data for Diallel Analysis using Hayman's Approach

Description

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

Usage

data(HaymanData)

Format

A data.frame with 256 rows and 4 variables.

Details

  • Cross1 Cross 1

  • Cross2 Cross 2

  • Rep Replicate

  • Yield Yield Response

Author(s)

Muhammad Yaseen ([email protected])

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. Test

Examples

data(HaymanData)

Analysis for Partial Diallel

Description

Analysis of Partial Diallel

Usage

PartialDiallel(y, Rep, Cross1, Cross2, data)

Arguments

y

Numeric Response Vector
Rep

Replicate as factor
Cross1

Cross 1 as factor
Cross2

Cross 2 as factor
data

A data.frame

Value

Means Means

ANOVA Analysis of Variance (ANOVA) table

Genetic.Components Genetic Components

General General

Specific Specific

Author(s)

  1. Pedro A. M. Barbosa ([email protected])

  2. Muhammad Yaseen ([email protected])

See Also

PartialDiallelData , Griffing , Hayman , GriffingData1 , GriffingData2 , GriffingData3 , GriffingData4

Examples

data(PartialDiallelData)
fm1 <-
  PartialDiallel(
      y      = y
    , Rep    = Rep
    , Cross1 = Cross1
    , Cross2 = Cross2
    , data   = PartialDiallelData
  )

fm1

Data for Partial Diallel Analysis

Description

Data for Partial Diallel Analysis

Usage

data(PartialDiallelData)

Details

  • Cross1 Cross 1

  • Cross2 Cross 2

  • Rep Replicate

  • Yield Yield Response

See Also

PartialDiallel , Griffing , Hayman , GriffingData1 , GriffingData2 , GriffingData3 , GriffingData4

Examples

data(PartialDiallelData)