GGEbiplot.hlp Index

Contents - Index

GGEbiplot.hlp Index

3D biplot
- Main menu BIPLOTS
3D-biplot
- 3D-biplot
3-way data
- Covariate-effect biplot based on genotypic values
- Genotype-by-(trait+environment) tables from 4-way data
- Genotype-by-trait table across environments
- Genotype-by-trait table across selected environments
- Genotype-by-trait table in an environment
4-way ANOVA
- ANOVA of 4-way data
4-way data
- Covariate-effect biplot based on genotypic values
- Genotype by location table from 4-way data
- Genotype-by-(trait+environment) tables from 4-way data
- Genotype-by-trait table across environments
- Genotype-by-trait table across selected environments
- Genotype-by-trait table in an environment
- Genotype-by-year*location table for a trait
4-way data options
- Main menu 4-WAY DATA
accessories
- Breeder's Kit
- Main menu ACCESSORIES
- Numerical Output
- Plot any two testers across entries
- Plot of Mean vs. Stability deviation
- Plot randomization Tool
AEA
- Average-tester axis
AEC
- Average-tester axis
- Mean Performance vs. Stability of entries
AMMI biplots
- Main menu BIPLOTS
AMMI1 biplot
- AMMI1 biplot
AMMI2 biplot
- Biplot based on double-centered data
analysis of covariates
- Covariate analysis
ANOVA
- ANOVA in a single environment (year-location combination)
- ANOVA of 4-way data
- ANOVA table
- Conventional statistics
- main effects
  - ANOVA-Main Effects
associated variables
- Find Associated Variables
- Pleiotrpoic effects of a marker
Association analysis
- Association and Regression Analysis
- Delete irrelevant variables
ATA
- Average-tester axis
- Mean Performance vs. Stability of entries
ATC
- Average-tester axis
- Discrimitiveness vs. representativeness of test environments
- Mean Performance vs. Stability of entries
Augmented
- Augmented Design
average environment
- Average tester
average tester
- Average tester
- Mean Performance vs. Stability of entries
average tester coordination
- Mean Performance vs. Stability of entries
average-environment coordination
- Mean Performance vs. Stability of entries
average-tester axis
- Average-tester axis
average-tester coordination
- Average-tester axis
Avoiding GE
- Avoiding/Exploiting GE through selection for explanatory traits
axes
- Four questions before trying to interpret a biplot
backgroud
- Change color
background
- Change color
background color
- Change the background color
balanced data
- Get balanced subset with regard to selected testers or entries
- Main menu DATA
balanced subset
- Generate a biplot based on the balanced subset
- Get partially balanced Subset
barley
- QTL identification - single trait in a single environment
biplot
- Four questions before trying to interpret a biplot
- Introduction to biplot analysis
- Start GGEbiplot
- What is a biplot
biplot analysis
- Biplot analysis vs. formal statistical analysis
- Independent Culling based on a biplot
- Main menu BIPLOT TOOLS
biplot of
- Biplot of PC1 vs. PC2
- Biplot of PC1 vs. PC3
- Biplot of PC2 vs. PC3
- Biplot of PC3 vs. PC4
- Biplot of PC5 vs. PC6
biplot size
- Change biplot size
biplot title
- Change the title of the biplot
biplots
- What if two PC's are not sufficient?
Breeder's
- Breeder's Toolbox
- Cross renaming
- File (picture) renaming
- Offspring Naming
- Test line renaming
Breeder's kit
- Breeder's Kit
- Plot randomization Tool
Canonical analysis
- VBV biplot
canonical biplot
- Generate a variable-by-varaible (VBV) biplot based on a two-way table
case
- Main menu FORMAT
centering method
- Biplot based on the original two-way table
- Main menu MODELS
- grand-mean centered
  - Data Centering methods
change case
- Change case
change color
- Change color
- Change the color of the biplot title
- Change the color of the entry labels
- Change the color of the lines
- Change the color of the tester labels
change color scheme
- Color scheme of the biplot
change font
- Change the font of the biplot title
- Change the font of the entry labels
- Change the font of the tester labels
check entry
- Rank all entries relative to a check
close
- Main menu FILE
Close biplot window
- Close
collearity
- Main menu ASSOCIATION
collinearity
- Delete variables on Log Ratio
collinearity among variables
- Remove collinear independent variables in multiple regression
color
- Main menu FORMAT
combine two testers
- Rank entries based on two testers
combined two-way tables
- Combined two-way tables
combining ability
- Diallel Data Analysis
- GCA and SCA of parents - diallel analysis
- Show the specific combining ability of a parent
comma-delimited text file
- Comma-delimited text file (*.csv)
- Data file types for GGEbiplot
comma-separated text file
- Data file types for GGEbiplot
Compare among three genotypes
- Compare among any three genotypes
Compare as packages
- Compare entries as packages of traits
Compare three entries
- Compare among any three entries
compare two entries
- Plot two entries across the testers
Compare two genotypes
- Compare two genotypes for performance in various environments
compare two testers
- Compare two entries with regard to various testers
- Plot two testers across the entries
Compare with a check
- Compare all genotypes with a user-specified check
completely multiplicative
- Biplot based on the original two-way table
complex two-way table
- Functions for Genotype by (Marker+Trait) data
compound two-way tables
- Functions for VARIOUS types of data
concepts
- Introduction to biplot analysis
connector
- Compare two entries with regard to various testers
Conruence coefficient
- Congruence coefficient
content
- CONTENT
conventional analyses
- Main menu ACCESSORIES
conventional statistics
- Conventional statistics
- Data Plotting
correlation
- r-p-t Convertor
- Conventional statistics
- Similarity among entries
correlation matrix
- Correlation matrix among testers
- Correlation matrix among the environments
cosine
- Similarity among entries
cosine-correlation equality
- Principles of biplot analysis
covariate analysis
- Covariate analysis
covariate effect
- Functions for genotype-by-(trait+environment) tables
- Generate a triat-association by environment biplot
covariate effect analysis
- Main menu ASSOCIATION
- VBV biplot
covariate effect biplot
- Covariate-effect biplot based on genotypic values
- Genotype-by-(trait+environment) tables from 4-way data
covariate effect table
- Generate a variable-by-varaible (VBV) biplot based on a two-way table
covariate effects
- Covariate-effect by environment biplot
covariate-effect
- Generate a triat-association by environment biplot
covariate-effect analysis
- Covariate-effect analysis
- Functions for genotype-by-(trait+environment) tables
- Generate a covariate-effect biplot from three-way or four-way data
- Generating the (marker-by-environment) table of marker-effects
- QTL identification - single trait in multiple environments
- Trait Association By Environment (TABE) biplot
covariate-effect biplot
- Biplot based on the original two-way table
- Eliminate less important markers from a QQE biplot
- Functions for genotype-by-(trait+environment) tables
- Generate a variable-by-varaible (VBV) biplot based on a two-way table
- Interpreting the trait-effect by environment biplot
- Linkage relation among selected markers in a QQE biplot
- Main menu ASSOCIATION
- Mega-environment classification based on a covariate-effect biplot
- Two-way table of covariate-effects
covariate-effect table
- Two-way table of covariate-effects
covariate-effect tables
- Main menu 4-WAY DATA
covarite-effect analysis
- Association (with a trait) by environment biplot
cross
- Cross renaming
data centering
- Data Transformation
data diagnosis
- Main menu ACCESSORIES
- Plot any two test environments across genotypes
Data File types
- Data file types for GGEbiplot
data format
- Any-way data input and analyses
- Four-way data - parallel
- Four-way data - serial
data input format
- Data formats for analysis using GGEbiplot
data manipulation
- Back to Original Data
- Back to Previous Subset
- Biplots based on any subset of data
- Diallel Data manipulation
- Main menu DATA
data path and name
- Show or hide data source
data plotting
- Data Plotting
- Main menu ACCESSORIES
- Plot any two entries across testers
- Plot any two test environments across genotypes
- Plot any two testers across entries
- Plot two entries across the testers
- Plot two testers across the entries
data scaling
- Data Transformation
data stratification
- Tester stratification
data transformation
- Data Transformation
- Main menu MODELS
data transposion
- Transpose a two-way table
delete entries
- Biplots based on any subset of data
- Generate a biplot based on the balanced subset
- Get partially balanced Subset
delete irrelevant variables
- Delete irrelevant variables
delete testers
- Biplots based on any subset of data
- Generate a biplot based on the balanced subset
- Get partially balanced Subset
Delete unwanted testers
- Delete unwanted variables
derived variables
- Derived values
diallel
- Diallel Data Analysis
- Functions for diallel cross data
diallel analysis
- Delete parents per se values - diallel data analysis
- Find the best entry-tester combinations in a diallel cross
- GCA and SCA of parents - diallel analysis
diallel cross
- Rank entries based on specific combining ability with a tester - diallel analysis
- Show the specific combining ability of a parent
Diallel crosses
- Diallel Data Analysis
Diallel data
- Diallel Data Analysis
diallel data analysis
- Complete the two-way table of a diallel cross dataset
- Diallel Data manipulation
- Remove reciporical effects - diallel analysis
di-genic interaction
- Include any interaction terms in the model
Discrimitiveness
- Discrimitiveness and representativeness of test environments
- Discrimitiveness power and representativeness of testers
- Discrimitiveness vs. representativeness of test environments
- Discrimitiveness vs. representativeness of testers
disease resistance
- Evaluate host genotypes for their general and specific resistance
double-centered
- Biplot based on double-centered data
- Data Centering methods
EGE biplot
- Biplot based on transposed data
entries
- Re-label the entries or testers
- What are entries and testers
entry
- What are entries and testers
entry evaluation
- Main menu BIPLOT TOOLS
entry index
- Show entries and/or testers as indices
Entry labeling
- Entries with FIRST N Letters
Entry labelling
- Entries with LAST N Letters
- Entries WITHOUT First N Letters
- Entries WITHOUT Last N Letters
entry labels
- Change color
entry ranking
- Mean and Stability of entries
- Rank entries based on two testers
entry vectors
- The relative importance of a marker or QTL
environment by trait biplot
- Environment-by-trait table
- Multivariate Biplot
environment by trait table
- Environment-by-trait table
environment-trait tables
- Environment-by-trait tables from a 4-way data
epistasis
- Include any interaction terms in the model
equalizer
- Compare two entries with regard to various testers
essential elements
- Four questions before trying to interpret a biplot
exit
- Main menu FILE
exit GGEbiplot
- Exit GGEbiplot
Experimental design
- Augmented Design
- Experimental Designs using GGEbiplot
- Incomplete Blocks Design
- Randomized Complete Blocks Design
- Row-Column Design
- Row-Nursery Design
explanatory traits
- Covariate-effect by environment biplot
- Functions for genotype-by-(trait+environment) tables
explanatory varaibles
- Generate a variable-by-varaible (VBV) biplot based on a two-way table
explanatory variables
- Functions for VARIOUS types of data
explantory variables
- Generate a triat-association by environment biplot
exploring GE
- Avoiding/Exploiting GE through selection for explanatory traits
file
- Main menu FILE
Find associaited variables
- Find Associated Markers
find associated variables
- Delete irrelevant variables
first fefw letters
- Entries with FIRST N Letters
first few letters
- Testers with LAST N Letters
Flip biplot
- Flip biplot horizontally
- Flip biplot vertically
font
- Main menu FORMAT
font bold
- Change Font
font italic
- Change Font
font name
- Change Font
font size
- Change font size of the entries and/or testers
- Change Font
format
- Change biplot size
- Change case
- Change color
- Change font size of the entries and/or testers
- Change Font
- Change the background color
- Change the color of the biplot title
- Change the color of the entry labels
- Change the color of the lines
- Change the color of the tester labels
- Change the font of the biplot title
- Change the font of the entry labels
- Change the font of the tester labels
- Change the title of the biplot
- Color scheme of the biplot
- Individual label Formatting
- Main menu FORMAT
four-way data
- Data formats for analysis using GGEbiplot
- Four-way data - parallel
- Four-way data - serial
- Main menu 4-WAY DATA
Full names
- Full names of the entries and testers
- Show full names
functions
- Main menu 4-WAY DATA
- Organization of functions in GGEbiplot
G+GE
- What is a GGE biplot
GCA
- Diallel Data Analysis
- Functions for diallel cross data
- GCA and SCA of parents - diallel analysis
- Mean Performance vs. Stability of entries
- Rank entries based on general combining ability - diallel analysis
GE biplot
- Biplot based on double-centered data
gene chips
- Functions for gene-by-chip tables (gene expresson data)
gene expression
- Functions for gene-by-chip tables (gene expresson data)
gene map
- Linear map among markers
gene mapping
- Functions for genotype-by-marker tables
general combining ability
- Rank entries based on general combining ability - diallel analysis
general resistance
- Evaluate host genotypes for their general and specific resistance
general virulence
- Evaluate pathogen strains for their general and specific virulence
genetic linkage
- Linkage relation among selected markers in a QQE biplot
genotype by environment
- Functions for genotype-by-(marker+environmnet) tables
genotype by environment*Trait table
- Genotype-by-environment*trait table
genotype by location biplot
- Genotype by location table from 4-way data
- Genotype-by-location table for any trait
genotype by location table
- Genotype-by-location table for any trait
genotype by marker
- Functions for genotype-by-(marker+environmnet) tables
genotype by marker + environment
- Functions for genotype-by-(marker+environmnet) tables
genotype by trait biplot
- Genotype-by-trait table across selected environments
- Genotype-by-trait table in an environment
- Multivariate Biplot
genotype by trait table
- Genotype-by-trait table across environments
genotype by year biplot
- Genetype-by-year table for a trait
Genotype by year*location table
- Genotype-by-year*location table for a trait
genotype classification
- Compound two-way tables
- Genotype-by-environment*trait table
genotype evaluation
- Genotype evaluation based on a GGE biplot
- Mean vs. stability of genotypes
- Rank genotypes based on performance in any given environment
- Rank genotypes based on performance in any two environments
- Show the specific adaptation of a genotype
- Which genotype won in which environment?
genotype ranking
- Discard genotypes based on performance in any environment
genotype-by-environment biplots
- Various Genotype-by-Environment Biplots
genotype-by-environment data
- Functions for genotype by environment data
genotype-by-trait biplot
- Functions for genotype-by-trait tables
genotype-by-trait data
- Functions for genotype-by-trait tables
genotype-by-trait+environment table
- Generate a triat-association by environment biplot
geograpic information system
- Functions for location-by-factor tables
GGE
- What is a GGE biplot
GGE biplot
- Functions for genotype by environment data
- Introduction to biplot analysis
- What is a GGE biplot
GGE pattern
- Mega-environment classification based on the GGE pattern
GGE1 biplot
- Biplot based on tester-centered data
GGE2 biplot
- Biplot based on tester Stdev standardized data
GGE3 biplot
- Biplot based on tester Stderr standardized data
GGEbiplot
- CONTENT
- Organization of functions in GGEbiplot
GH biplot
- Singular value partitioning
GIS
- Functions for location-by-factor tables
grand-mean centered biplot
- Biplot based on grand-mean centered data
group environments
- Group environments based on winning genotypes
Guideline
- Show/Hide the Guidelines
heterosis
- Functions for diallel cross data
heterotic groups
- Functions for diallel cross data
hide labels
- Main menu VIEW
higher order biplots
- Main menu BIPLOTS
host-pathogen interaction
- Evaluate pathogen strains for their general and specific virulence
- Functions for host by pathogen data
- Interaction between host genotypes and pathogen strains
how many PC's are needed
- How many principal components are needed?
- Information Content
hybred
- Functions for Inbred-by-tester tables
hypothesis test
- Biplot analysis vs. formal statistical analysis
ICBD
- Incomplete Blocks Design
ideal entry
- Mean and Stability of entries
- Rank genotypes based on both mean performance and stability
Ideal genotype
- Rank genotypes based on both mean performance and stability
ideal test environments
- Discrimitiveness and representativeness of test environments
ideal tester
- Discrimitiveness power and representativeness of testers
Importance of a PC
- How many principal components are needed?
inbred
- Functions for Inbred-by-tester tables
Independent culling
- Breeder's Kit
- Independent Culling based on a biplot
- Independent Selection
- Multi-Trait Selection Tool
independent selection
- Breeder's Kit
- Independent Culling
- Multi-Trait Selection Tool
index selection
- Index Selection
- Multi-Trait Selection Tool
indirect selection
- Covariate-effect by environment biplot
Information Content
- How many principal components are needed?
- Information Content
inner-product
- Principles of biplot analysis
input
- Any-way data input and analyses
- Main menu FILE
input data format
- Data formats for analysis using GGEbiplot
install
- Install GGEbiplot
interaction terms in multiple regression
- Include any interaction terms in the model
Interactive PC
- Biplot based on double-centered data
Interpreting GE
- Avoiding/Exploiting GE through selection for explanatory traits
IPC
- Biplot based on double-centered data
JK biplot
- Singular value partitioning
kernel weight
- QTL identification - single trait in a single environment
labels
- Re-label the entries or testers
last few letters
- Entries with LAST N Letters
ledend
- Show entries and/or testers as indices
limitations
- Biplot analysis vs. formal statistical analysis
limiting variables
- Find Associated Markers
linear map
- Linear map among markers
- Linear Map of Testers
lines
- Change color
linkage
- Functions for genotype-by-marker tables
- Identify markers closely associated with a target marker
- Linkage relation among selected markers in a QQE biplot
Linked markers
- Find Associated Variables
location by trait biplot
- Location-by-trait-table
location by trait table
- Location-by-trait-table
location cluster
- Functions for location-by-factor tables
log file
- Correlation matrix among testers
- Log file
log ratio
- Delete variables on Log Ratio
- Log ratio for removing colliearity among variables
- Main menu ASSOCIATION
- Remove collinear independent variables in multiple regression
Main effects ANOVA
- ANOVA of 4-way data
main menu
- Main menu BIPLOT TOOLS
- Organization of functions in GGEbiplot
marker
- Identify markers closely associated with a target marker
marker by environment biplot
- Determining the number of QTL
- Generate a QQE biplot
- Type I error concentric circles
marker by environment interaction
- Screening for relevant markers
marker by environment table
- Generating the (marker-by-environment) table of marker-effects
marker linkage
- Identify markers closely associated with a target marker
marker-by-trait biplot: QQT biplot
- QTL identification - multiple traits in a single environment
markers
- Functions for Genotype by (Marker+Trait) data
ME
- What are mega-environments
mean
- Mean vs. stability of genotypes
mean and stability
- Mean and Stability of entries
- Mean Performance vs. Stability of entries
- Plot of Mean vs. Stability deviation
- Rank genotypes based on both mean performance and stability
- Rank genotypes based on mean performance across all environments
mean performance
- Mean Performance vs. Stability of entries
mean scaled
- Data Scaling methods
mega-environment
- Avoiding/Exploiting GE through selection for explanatory traits
- Group environments based on winning genotypes
- Mega-environment classification based on a covariate-effect biplot
- Mega-environment classification based on the GGE pattern
- Mega-environment classification based on the QQE pattern
- What are mega-environments
Mega-Environment Classification
- Mega-Environment vs. Which-Won-Where
menu
- Organization of functions in GGEbiplot
merits of GGEbiplot
- Why use GGEbiplot software
microarray data
- Functions for gene-by-chip tables (gene expresson data)
Mising cells
- How does GGEbiplot treat missing cells
missing cells
- Fill Missing Cells
Missing values
- Fill Missing Cells
model
- What if two PC's are not sufficient?
model 0
- Biplot based on grand-mean centered data
model 4
- Biplot based on double-centered data
models
- Data Centering methods
- Data Scaling methods
- Four questions before trying to interpret a biplot
- Main Menu MODELS - old
- Main menu MODELS
multiple comparison
- Conventional statistics
multiple environments
- Determining the number of QTL
- Generating the (marker-by-environment) table of marker-effects
- QTL identification - single trait in multiple environments
- Screening for relevant markers
- Type I error concentric circles
multiple linear regression
- Functions for multiple regression data
- Multiple linear regression
multiple regression
- Association and Regression Analysis
- Conduct multiple regression
- Delete variables on Log Ratio
- Include any interaction terms in the model
- Include any quadratic terms in the model
- QTL identification - single trait in a single environment
multi-trait selection
- Breeder's Kit
- Index Selection
multivariate analyses
- Main menu ASSOCIATION
multivariate biplot
- Functions for genotype-by-trait tables
- Multivariate Biplot
multple regression
- Main menu ASSOCIATION
multple traits
- QTL identification - multiple traits in a single environment
mutlivariate data
- Functions for VARIOUS types of data
New project
- New project
Number of PC
- Information Content
numerical output
- Log file
- Numerical Output
numerical outputs
- Main menu ACCESSORIES
offspring
- Offspring Naming
Open text data file
- Open a text data file
original data
- Back to Original Data
output
- Main menu FILE
parallel columns
- Three-way data - parallel
parallel data
- Data formats for analysis using GGEbiplot
- Four-way data - parallel
partially balanced
- Get partially balanced Subset
pattern
- Biplot analysis vs. formal statistical analysis
- What are patterns?
pattern discovery
- Biplot analysis vs. formal statistical analysis
PC1 vs. PC2
- Biplot of PC1 vs. PC2
PC1 vs. PC3
- Biplot of PC1 vs. PC3
PC2 vs. PC3
- Biplot of PC2 vs. PC3
PC3 vs. PC4
- Biplot of PC3 vs. PC4
PC5 vs. PC6
- Biplot of PC5 vs. PC6
PCA
- Principal component analysis
- Singular value decomposition
penotype by trait table
- Genotype*environment-by-trait table
permutation
- How permutation is conducted
perpendicular line
- Which-won-where
phenotype-by-trait
- Compound two-way tables
phenotypic data
- Association (with a trait) by environment biplot
physical conditions
- Functions for location-by-factor tables
picture
- File (picture) renaming
pleiotropic effect
- Find traits associated with a single locus (Pleiotropic effect)
- Pleiotrpoic effects of a marker
pleiotropy
- Pleiotrpoic effects of a marker
plot tile
- Change color
plot two entries
- Plot any two entries across testers
polygon
- Which-won-where
prabability' t-test
- r-p-t Convertor
previous subset
- Back to Previous Subset
primary biplot
- Biplot of PC1 vs. PC2
- Main menu BIPLOTS
- What if two PC's are not sufficient?
principal component analysis
- Principal component analysis
principles of biplot
- Principles of biplot analysis
Principles of biplot analysis
- Introduction to biplot analysis
print
- Main menu FILE
Print biplot
- Print biplot
QQE
- Functions for genotype-by-(marker+environmnet) tables
QQE biplot
- Biplot based on the original two-way table
- Covariate-effect analysis
- Eliminate less important markers from a QQE biplot
- Generate a covariate-effect biplot from three-way or four-way data
- Generate a QQE biplot
- Generate a variable-by-varaible (VBV) biplot based on a two-way table
- Interpret a QQE biplot
- Linkage relation among selected markers in a QQE biplot
- Main menu ASSOCIATION
- Marker (QTL) effect-by-environment biplot - QQE biplot
- The relative importance of a marker or QTL
- Trait Association By Environment (TABE) biplot
- VBV biplot
QQE pattern
- Mega-environment classification based on the QQE pattern
QTL
- Marker (QTL) effect-by-environment biplot - QQE biplot
- QTL identification - single trait in multiple environments
- Remove collinear independent variables in multiple regression
QTL by environent biplot
- Marker (QTL) effect-by-environment biplot - QQE biplot
QTL by environment biplot
- Generate a QQE biplot
- Mega-environment classification based on the QQE pattern
QTL effect
- The relative importance of a marker or QTL
QTL identification
- Determining the number of QTL
- Eliminate less important markers from a QQE biplot
- Functions for multiple regression data
- Generating the (marker-by-environment) table of marker-effects
- Linkage relation among selected markers in a QQE biplot
- QTL identification - single trait in multiple environments
- Screening for relevant markers
- Type I error concentric circles
QTL mapping
- Find Associated Markers
- Functions for Genotype by (Marker+Trait) data
- Functions for genotype-by-(marker+environmnet) tables
- Include any interaction terms in the model
- QTL identification - multiple traits in a single environment
- QTL identification - single trait in a single environment
- QTL identification - single trait in multiple environments
QTL-by-environment data
- The relative importance of a marker or QTL
QTL-by-environment interaction
- Functions for genotype-by-(marker+environmnet) tables
- Interpret a QQE biplot
QTL-environment interaction
- Marker (QTL) effect-by-environment biplot - QQE biplot
quadratic terms
- Include any quadratic terms in the model
randomization
- Plot randomization Tool
Rank entries
- Rank all entries relative to a check
- Rank entries based on any given tester
Rank genotypes
- Rank genotypes based on performance in any given environment
- Rank genotypes based on performance in any two environments
rank testers
- Rank all entries relative to a check
- The relative performance of an entry relative to individual testers
RCDB
- Randomized Complete Blocks Design
reading data
- Start GGEbiplot
redundant environments
- Identify redundant environments or the need for more test environments
redundant testers
- Identify redundant environments or the need for more test environments
- Show relationship among testers
references
- References on biplot analysis
refresh
- Remove backgorund noise
regression
- Conventional statistics
relabeling
- Main menu VIEW
relabling
- Testers with FIRST N Letters
relation among enivronments
- Show relationship among test environments
relation among testers
- Show relationship among test environments
relative adaptation
- Show the specific adaptation of a genotype
- The relative performance of an entry relative to individual testers
remove testers
- Delete unwanted testers manually
renaming
- Cross renaming
- File (picture) renaming
- Offspring Naming
- Test line renaming
representativeness
- Discrimitiveness and representativeness of test environments
- Discrimitiveness power and representativeness of testers
- Discrimitiveness vs. representativeness of test environments
- Discrimitiveness vs. representativeness of testers
response variables
- Functions for VARIOUS types of data
- Generate a variable-by-varaible (VBV) biplot based on a two-way table
reverse sign
- Reverse the sign of a variable
- Reverse the sign of all testers
- Reverse the sign of one or all testers
Row-column design
- Row-Column Design
S.V.P.
- Singular value decomposition
- Singular value partitioning
save
- Main menu FILE
save biplot image
- Print biplot
- Save biplot image
SCA
- Diallel Data Analysis
- Functions for diallel cross data
- GCA and SCA of parents - diallel analysis
- Rank entries based on specific combining ability with a tester - diallel analysis
scaling
- Data Scaling methods
scaling method
- Main menu MODELS
secondary biplots
- Main menu BIPLOTS
selection
- Independent Culling
- Independent Selection
- Index Selection
- Multi-Trait Selection Tool
- Selection Index
selection index
- Breeder's Kit
- Index Selection
- Multi-Trait Selection Tool
- Selection Index
serial data
- Data formats for analysis using GGEbiplot
- Four-way data - serial
- Three-way data - serial
- Two-way table - serial
show both entries and testers
- Show both entries and testers
show entries only
- Hide testers and show entries only
show labels
- Main menu VIEW
show testers only
- Hide entries and show testers only
show/hide biplot title
- Show or hide the biplot title
show/hide logo
- Show or hide the logo
singular value decomposition
- Singular value decomposition
singular value partitioning
- Entry-focused SVP
- Singular value decomposition
- Singular value partitioning
size
- Main menu FORMAT
software
- Organization of functions in GGEbiplot
specific combining ability
- Rank entries based on specific combining ability with a tester - diallel analysis
specific resistance
- Evaluate host genotypes for their general and specific resistance
specific virulence
- Evaluate pathogen strains for their general and specific virulence
stability
- Mean Performance vs. Stability of entries
- Mean vs. stability of genotypes
Start
- Start GGEbiplot
statistical analysis
- Biplot analysis vs. formal statistical analysis
stderr scaled
- Data Scaling methods
stderr-scaled
- Biplot based on tester Stderr standardized data
stderr-standardized
- Biplot based on tester Stderr standardized data
stdev scaled
- Data Scaling methods
stdev-scaled
- Biplot based on tester Stdev standardized data
stdev-standarded
- Biplot based on tester Stdev standardized data
steps of multiple regression
- Conduct multiple regression
stratification
- Entry stratification
subset
- Biplots based on any subset of data
- Delete unwanted testers manually
- Entry stratification
- Generate a biplot based on the balanced subset
- Get any Subset
- Get balanced subset with regard to selected testers or entries
- Subset
- Tester stratification
subsets
- What if two PC's are not sufficient?
subsetting
- Biplots based on any subset of data
- Compare among any three entries
- Delete unwanted testers manually
- Get any Subset
- Main menu DATA
Superiority index
- YREM (Superiority Index)
SVD
- Singular value decomposition
SVP
- Entry-focused SVP
- Four questions before trying to interpret a biplot
- Singular value decomposition
- Singular value partitioning
- Symmetrical SVP
- Tester-focused SVP
switch biplot axes
- Switch biplot axes
TABE biplot
- Association (with a trait) by environment biplot
- Associations (among traits) by environment biplot
Test environment evaluation
- Correlation matrix among the environments
- Test environment evaluation based on the GGE biplot
test relations
- Show relationship among test environments
tester
- What are entries and testers
tester evaluation
- Correlation matrix among the environments
- Discrimitiveness power and representativeness of testers
- Discrimitiveness vs. representativeness of test environments
- Discrimitiveness vs. representativeness of testers
- Main menu BIPLOT TOOLS
tester index
- Show entries and/or testers as indices
Tester labelling
- Testers with LAST N Letters
- Testers WITHOUT First N Letters
- Testers WITHOUT Last N Letters
tester labels
- Change color
tester relations
- Identify redundant environments or the need for more test environments
- Show relationship among testers
tester subsetting
- Delete unwanted testers manually
tester vector view
- Show relationship among test environments
- Show relationship among testers
tester vectors
- Similarity among entries
tester-centered
- Biplot based on tester-centered data
- Data Centering methods
testers
- Functions for Inbred-by-tester tables
- Re-label the entries or testers
- What are entries and testers
three-way data
- Data formats for analysis using GGEbiplot
- Three-way data - parallel
- Three-way data - serial
title
- Main menu FORMAT
trait assocaition by environment biplot
- Trait Association By Environment (TABE) biplot
trait association
- Associations (among traits) by environment biplot
trait relations
- Functions for genotype-by-trait tables
trait-by-environment biplot
- Generate a triat-association by environment biplot
trait-effect biplot
- Interpreting the trait-effect by environment biplot
- Mega-environment classification based on a covariate-effect biplot
trait-marker associations
- Find traits associated with a single locus (Pleiotropic effect)
traits
- Functions for Genotype by (Marker+Trait) data
transpose
- Biplot based on transposed data
transposion
- Transpose a two-way table
two-way data
- Data formats for analysis using GGEbiplot
- Functions for VARIOUS types of data
- Two-way table - serial
two-way data format
- Two-way Table - matrix
two-way tables
- Functions for VARIOUS types of data
- Main menu 4-WAY DATA
- Simple two-way tables
type I error
- Type I error concentric circles
univariate biplot
- Univariate Biplot
variable by variable biplot
- VBV biplot
various biplots
- Main menu BIPLOTS
VBV biplot
- Covariate-effect analysis
- Covariate-effect by environment biplot
- VBV biplot
VBV biplot analysis
- Covariate-effect analysis
- VBV biplot
vector
- Vectors
vector length
- The relative importance of a marker or QTL
vertex
- Polynomial regression
verticle resistance
- Interaction between host genotypes and pathogen strains
View
- Main menu VIEW
- Re-label the entries or testers
V-V biplot
- Covariate-effect analysis
which-won-what
- Show the best genotypes for each environment
- Which genotype is the best for which trait
- Which genotype is the poorest in what
which-won-where
- Compare among any three entries
- Group environments based on winning genotypes
- Polynomial regression
- Show the best genotypes for each environment
- Which genotype won in which environment?
- Which-won-where
Which-Won-Where Pattern
- Mega-Environment vs. Which-Won-Where
why use GGEbiplot
- Why use GGEbiplot software
winning genotype
- Polynomial regression
without first few letters
- Entries WITHOUT First N Letters
- Testers WITHOUT First N Letters
without last few letters
- Entries WITHOUT Last N Letters
- Testers WITHOUT Last N Letters
year by location biplot
- Year-by-location table for any trait
year by trait biplot
- Year-by-trait table
year by trait table
- Year-by-trait table
YREM
- YREM (Superiority Index)