Tool for Stability Indices Calculation.
toolStability: Tool for Stability Indices Calculation 
License: GPL-3
Wang, T-C. and Chen, T-W.
Description
Tools to calculate stability indices with parametric, non-parametric and probabilistic approaches. The basic data format requirement for ‘toolStability’ is a data frame with 3 columns including numeric trait values, genotype,and environmental labels. Output format of each function is the dataframe with chosen stability index for each genotype. Function “table_stability” offers the summary table of all stability indices in this package. There are 11 stability indices in this package.
This R package toolStability is part of the main publication: Wang, Casadebaig and Chen (2023) doi:10.1007/s00122-023-04264-7. Analysis pipeline for main publication can be found on github: https://github.com/Illustratien/Wang_2023_TAAG.
Sample dataset in this package is derived from another publication: Casadebaig P, Zheng B, Chapman S et al. (2016) doi:10.1371/journal.pone.0146385. For detailed documentation of dataset, please see on Zenodo doi:10.5281/zenodo.4729636.
Installation
The package can be installed from CRAN as follows:
install.packages('toolStability', dependencies=TRUE)
The development version can be installed from github as follows:
if (!require('devtools')) install.packages('devtools')
devtools::install_github("Illustratien/toolStability")
# or
if (!require('remotes')) install.packages('remotes')
remotes::install_github("Illustratien/toolStability")
Tutorial
There are 11 stability indices in this package. A detailed tutorial with examples and references: click here.
What’s new
To know whats new in this version type:
news(package='toolStability')
Links
Main publication analysis and visualization pipeline
Dataset documentation on Zenodo
Package documentation on Zenodo
Citing toolStability
To cite the methods in the package please use:
Wang, TC., Casadebaig, P. & Chen, TW. More than 1000 genotypes are required to derive robust relationships between yield, yield stability and physiological parameters: a computational study on wheat crop. Theor Appl Genet 136, 34 (2023). https://doi.org/10.1007/s00122-023-04264-7