{
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  "Package": "rYWAASB",
  "Type": "Package",
  "Title": "Simultaneous Selection by Trait and WAASB Index",
  "Version": "0.3",
  "Date": "2025-05-22.",
  "Authors@R": "person(family=\"Arminian\", given =\"Ali\", email=\"abeyran@gmail.com\", role = c(\"aut\", \"cre\", \"cph\"), comment = c(ORCID = \"0000-0003-4749-6085\"))",
  "Maintainer": "Ali Arminian <abeyran@gmail.com>",
  "Description": "This tool proposes a new ranking algorithm that utilizes a\n\"Y*WAASB\" biplot generated by the 'metan'. The aim of the\ncurrent package is to effectively distinguish the top-ranked\ngenotypes in MET (Multi-Environmental Trials). For a detailed\nexplanation of the process of obtaining \"WAASB\", \"WAASBY\"\nindices, and a \"Y*WAASB\" biplot, refer to the manual included\nin this package as well as the study by Olivoto & Lúcio (2020)\n<doi:10.1111/2041-210X.13384>. In this context, \"WAASB\" refers\nto the \"Weighted Average of Absolute Scores\" provided by\nOlivoto et al. (2019) <doi:10.2134/agronj2019.03.0220>, which\nquantifies the stability of genotypes across different\nenvironments using linear mixed-effect models. To run the\npackage, you need to extract the \"WAASB\" and \"WAASBY\"\ncoefficients using the 'metan' and apply them. This tool\nutilizes PCA (Principal Component Analysis) and differentiates\nthe entries which may be genotypes, hybrids, varieties, etc\nusing \"WAASB\", \"WAASBY\", and a combination of the specified\ntrait and WAASB index.",
  "License": "GPL-3",
  "URL": "https://github.com/abeyran/rYWAASB",
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  "Author": "Ali Arminian [aut, cre, cph] (ORCID:\n<https://orcid.org/0000-0003-4749-6085>)",
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  "Repository": "https://abeyrann.r-universe.dev",
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      "title": "Simultaneous Selection by Trait and WAASB Index",
      "topics": [
        "rYWAASB-package",
        "rYWAASB"
      ]
    },
    {
      "page": "bar_plot1",
      "title": "The first barplot of the ranks of genotypes",
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        "bar_plot1"
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    },
    {
      "page": "bar_plot2",
      "title": "The second barplot of the ranks of genotypes",
      "topics": [
        "bar_plot2"
      ]
    },
    {
      "page": "data_ge",
      "title": "Dataset3: a tibble containing ENV, GEN, REP factors and GY(grain yield) and HM agronomic traits from the 'metan' package.",
      "topics": [
        "data_ge"
      ]
    },
    {
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      "topics": [
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      ]
    },
    {
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        "maize"
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      "title": "Simultaneous Selection by Trait and WAASB Index",
      "author": "Ali Arminian",
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        "1-Introduction",
        "The WAASB and WAASBY objects",
        "2- How to apply the package",
        "Applying the rYWAASB package. Ranking table:",
        "Drawing the first plot bar_plot1:",
        "Drawing the second plot bar_plot2:",
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        "Designing the cluster analysis on data and define the optimum number of clusters uning The Average Silhouette Method. The details of this method is given in the description and details parts of the function nbclust(). For running the cluster analysis by menas of shipunov package (courtesy of late professor Alexy Shipunov) act as:",
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