Phenotypic_Correlation_app {TBA}R Documentation

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()

[Package TBA version 0.1.0 Index]