R package metan

Photo by Tiago Olivoto

metan (multi-environment trials analysis) provides useful functions for analyzing multi-environment trial data using parametric and nonparametric methods. The package will help you to:

  • Inspect data for possible common errors;
  • Manipulate rows and columns;
  • Manipulate numbers and strings;
  • Compute descriptive statistics;
  • Compute within-environment analysis of variance;
  • Compute AMMI analysis with prediction considering different numbers of interaction principal component axes;
  • Compute AMMI-based stability indexes;
  • Compute GGE biplot analysis;
  • Compute BLUP-based stability indexes;
  • Compute variance components and genetic parameters in mixed-effect models;
  • Perform cross-validation procedures for AMMI-family and BLUP models;
  • Compute parametric and nonparametric stability statistics
  • Implement biometrical models

Installation

Install the released version of metan from CRAN with:

install.packages("metan")

Or install the development version from GitHub with:

devtools::install_github("TiagoOlivoto/metan")

# To build the HTML vignette use
devtools::install_github("TiagoOlivoto/metan", build_vignettes = TRUE)

Note: If you are a Windows user, you should also first download and install the latest version of Rtools.

For the latest release notes on this development version, see the NEWS file.

Cheatsheet

Citation

To cite metan in your publications, please, use the official reference paper:

Olivoto, T., and Lúcio, A.D. (2020). metan: an R package for multi-environment trial analysis. Methods Ecol Evol. Accepted Author Manuscript doi:10.1111/2041-210X.13384

A BibTeX entry for LaTeX users is

  @Article{Olivoto2020,
    author = {Tiago Olivoto and Alessandro Dal'Col L{'{u}}cio},
    title = {metan: an R package for multi-environment trial analysis},
    journal = {Methods in Ecology and Evolution},
    volume = {n/a},
    number = {n/a},
    year = {2020},
    doi = {10.1111/2041-210X.13384},
    url = {https://besjournals.onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.13384},
  }
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