Type: Package
Title: Collection of 'shiny' Apps for Tree Breeding Analysis
Version: 0.1.0
Description: A collection of interactive 'shiny' applications for performing comprehensive analyses in the field of tree breeding and genetics. The package is designed to assist users in visualizing and interpreting experimental data through a user-friendly interface. Each application is launched via a simple function, and users can upload data in 'Excel' format for analysis. For more information, refer to Singh, R.K. and Chaudhary, B.D. (1977, ISBN:9788176633079).
Maintainer: Bijoy Chanda <bijoychanda08@gmail.com>
License: GPL-3
Encoding: UTF-8
Imports: shiny, ggplot2, readxl, reshape2, shinybusy
NeedsCompilation: no
Suggests: testthat (≥ 3.0.0)
Config/testthat/edition: 3
Packaged: 2025-05-07 18:32:57 UTC; Bijoy Chanda
Author: K. Rajarajan [aut, ctb], Bijoy Chanda [aut, ctb, cre], A. Arunachalam [ctb], A. K. Handa [ctb]
Repository: CRAN
Date/Publication: 2025-05-09 14:00:02 UTC

Analysis of Variance (ANOVA)

Description

ANOVA_app() function opens an interactive and user friendly Shiny application that enables users to perform Analysis of Variance (ANOVA) for multi-trait experimental data based on the Randomized Block Design (RBD) by uploading an Excel file.

Usage

ANOVA_app()

Details

The application is designed to perform ANOVA for datasets based on the Randomized Block Design (RBD).

Users can upload an Excel file (.xlsx or .xls) containing data for multiple traits. After uploading the file, users need to click the "Analyze" button.

Results are presented in a tabular format showing sources of variation, their respective degrees of freedom (Df), and the Mean Sum of Squares for each trait. Significance is also indicated.

The output table is downloadable in CSV format.

Value

Opens a user-friendly interactive shiny application for performing ANOVA on experimental data.

Data Format

The uploaded Excel file should be formatted as follows:

Trait names should be concise. Example:

Note: The uploaded file name should not contain spaces. For example, use Sample_Data.xlsx instead of Sample Data.xlsx.

An example Excel file is available for download using the Download Example Data button within the application.

The example dataset includes:

References

Singh, R. K., & Chaudhary, B. D. (1977). Biometrical Methods in Quantitative Genetic Analysis.

Examples

if(interactive()) ANOVA_app()

Genetic Variability Parameters

Description

Genetic_Variability_Parameters_app() function opens an interactive and user friendly Shiny application that enables users to estimate genetic variability parameters for multi-trait experimental data based on the Randomized Block Design (RBD).

Usage

Genetic_Variability_Parameters_app()

Details

The application is designed to calculate genetic variability parameters for datasets based on the Randomized Block Design (RBD).

Users can upload an Excel file (.xlsx or .xls) containing data for multiple traits. After uploading the file, users need to click the "Analyze" button.

The results are displayed in a tabular format including the following parameters for each trait:

The output table is downloadable in CSV format.

Value

Opens a user-friendly interactive Shiny application for calculating genetic variability parameters from experimental data.

Data Format

The uploaded Excel file should be formatted as follows:

Trait names should be concise. Example:

Note: The uploaded file name should not contain spaces. For example, use Sample_Data.xlsx instead of Sample Data.xlsx.

An example Excel file is available for download using the Download Example Data button within the application.

The example dataset includes:

References

Singh, R. K., & Chaudhary, B. D. (1977). Biometrical Methods in Quantitative Genetic Analysis.
Johnson, Herbert W., H. F. Robinson, and R. E. Comstock. (1955). Estimates of genetic and environmental variability in soybeans. Agronomy Journal, 47(7), 314-318.

Examples


if(interactive()) Genetic_Variability_Parameters_app()

Genotypic Correlation

Description

Genotypic_Correlation_app() function opens an interactive and user-friendly Shiny application that enables users to compute genotypic correlation coefficients among multiple traits from experimental data.

Usage

Genotypic_Correlation_app()

Details

The application is designed to perform genotypic correlation analysis across multiple traits using experimental data.

Users can upload an Excel file (.xlsx or .xls) containing observations for several genotypes and traits. After uploading the file, users need to click the "Analyze" button.

The output is presented as a matrix showing the genotypic correlation coefficients between traits. A significance indication is provided along with an option to visualize the matrix as a heatmap plot.

The correlation table can be downloaded in CSV format, and the heatmap plot as an image in JPEG and PNG format

Note: The analysis is based on the Randomized Block Design (RBD).

Value

Opens a user-friendly interactive Shiny application for performing genotypic correlation analysis.

Data Format

The uploaded Excel file should be formatted as follows:

Trait names should be concise. Example:

Note: The uploaded file name should not contain spaces. For example, use Sample_Data.xlsx instead of Sample Data.xlsx.

An example Excel file is available for download using the Download Example Data button within the application.

The example dataset includes:

References

Singh, R. K., & Chaudhary, B. D. (1977). Biometrical Methods in Quantitative Genetic Analysis.
Dewey, D. R., & Lu, K. H. (1959). A Correlation and Path-Coefficient Analysis of Components of Crested Wheatgrass Seed Production.Agronomy Journal, 51(9), 515-518.
Rajarajan, K., & K. Ganesamurthy(2014). Genetic diversity of sorghum [Sorghum bicolor (L.)] germplasm for drought tolerance. Range Management and Agroforestry, 35(2), 256-262.

Examples

if(interactive()) Genotypic_Correlation_app()

Genotypic Path

Description

Genotypic_Path_app() function opens an interactive and user-friendly Shiny application that enables users to perform genotypic path analysis.

Usage

Genotypic_Path_app()

Details

The application is designed to perform genotypic path analysis using experimental data.

Users can upload an Excel file (.xlsx or .xls) containing observations for several genotypes and traits. After uploading the file users should click the "Analyze" button.

The output includes:

The result table can be downloaded in CSV format.

Note: The analysis is based on the Randomized Block Design (RBD).

Value

Opens a user-friendly interactive Shiny application for performing genotypic path analysis.

Data Format

The uploaded Excel file should be formatted as follows:

Trait names should be concise. Example:

Note: The uploaded file name should not contain spaces. For example, use Sample_Data.xlsx instead of Sample Data.xlsx.

An example Excel file is available for download using the Download Example Data button within the application.

The example dataset includes:

References

Singh, R. K., & Chaudhary, B. D. (1977). Biometrical Methods in Quantitative Genetic Analysis.
Dewey, D. R., & Lu, K. H. (1959). A Correlation and Path-Coefficient Analysis of Components of Crested Wheatgrass Seed Production.Agronomy Journal, 51(9), 515-518.

Examples

if(interactive()) Genotypic_Path_app()

Phenotypic Correlation

Description

Phenotypic_Correlation_app() function opens an interactive and user-friendly Shiny application that enables users to compute phenotypic correlation coefficients among multiple traits experimental data.

Usage

Phenotypic_Correlation_app()

Details

The application is designed to perform phenotypic correlation analysis across multiple traits using experimental data.

Users can upload an Excel file (.xlsx or .xls) containing observations for several genotypes and traits. After uploading the file, users need to click the "Analyze" button.

The output is presented as a matrix showing the phenotypic correlation coefficients between traits. A significance indication is provided along with an option to visualize the matrix as a heatmap plot.

The correlation table can be downloaded in CSV format, and the heatmap plot as an image in JPEG and PNG format.

Note: The analysis is based on the Randomized Block Design (RBD).

Value

Opens a user-friendly interactive Shiny application for performing phenotypic correlation analysis.

Data Format

The uploaded Excel file should be formatted as follows:

Trait names should be concise. Example:

Note: The uploaded file name should not contain spaces. For example, use Sample_Data.xlsx instead of Sample Data.xlsx.

An example Excel file is available for download using the Download Example Data button within the application.

The example dataset includes:

References

Singh, R. K., & Chaudhary, B. D. (1977). Biometrical Methods in Quantitative Genetic Analysis.
Dewey, D. R., & Lu, K. H. (1959). A Correlation and Path-Coefficient Analysis of Components of Crested Wheatgrass Seed Production.Agronomy Journal, 51(9), 515-518.
Rajarajan, K., & K. Ganesamurthy(2014). Genetic diversity of sorghum [Sorghum bicolor (L.)] germplasm for drought tolerance. Range Management and Agroforestry, 35(2), 256-262.

Examples

if(interactive()) Phenotypic_Correlation_app()

Phenotypic Path

Description

Phenotypic_Path_app() function opens an interactive and user-friendly Shiny application that enables users to perform phenotypic path analysis.

Usage

Phenotypic_Path_app()

Details

The application is designed to perform phenotypic path analysis using experimental data.

Users can upload an Excel file (.xlsx or .xls) containing observations for several genotypes and traits. After uploading the file users should click the "Analyze" button.

The output includes:

The result table can be downloaded in CSV format.

Note: The analysis is based on the Randomized Block Design (RBD).

Value

Opens a user-friendly interactive Shiny application for performing phenotypic path analysis.

Data Format

The uploaded Excel file should be formatted as follows:

Trait names should be concise. Example:

Note: The uploaded file name should not contain spaces. For example, use Sample_Data.xlsx instead of Sample Data.xlsx.

An example Excel file is available for download using the Download Example Data button within the application.

The example dataset includes:

References

Singh, R. K., & Chaudhary, B. D. (1977). Biometrical Methods in Quantitative Genetic Analysis.
Dewey, D. R., & Lu, K. H. (1959). A Correlation and Path-Coefficient Analysis of Components of Crested Wheatgrass Seed Production.Agronomy Journal, 51(9), 515-518.

Examples

if(interactive()) Phenotypic_Path_app()