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/tree/V1.0.0.

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

Main publication analysis pipeline

Dataset documentation

CRAN page

Package documentation

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