Provides tools for the analysis of multi-environment agronomic 
    trials, with a specific focus on plant breeding experiments. 
    Implements the Additive Main effects and Multiplicative Interaction 
    (AMMI) model (Gauch, 1992, ISBN:9780444892409) and the Site Regression 
    (SREG) model (Cornelius, 1996, <doi:10.1201/9780367802226>). To ensure 
    reliable results even with outliers or missing data, it includes robust 
    versions of AMMI (Rodrigues et al., 2016, 
    <doi:10.1093/bioinformatics/btv533>) and SREG (Angelini et al., 2022, 
    <doi:10.1080/15427528.2022.2051217>). Furthermore, the package offers 
    advanced imputation techniques for multi-environment data, covering 
    classical methodologies (Arciniegas-Alarcón et al., 2014, 
    <doi:10.2478/bile-2014-0006>) and recently published imputation methods 
    for MET data (Angelini et al., 2024, <doi:10.1007/s10681-024-03344-z>).

Classes and methods for handling genetic data. Includes
        classes to represent genotypes and haplotypes at single markers
        up to multiple markers on multiple chromosomes. Function
        include allele frequencies, flagging homo/heterozygotes,
        flagging carriers of certain alleles, estimating and testing
        for Hardy-Weinberg disequilibrium, estimating and testing for
        linkage disequilibrium, ...

Finds subsets of sets of genotypes with a high Heterozygosity, and Mean of Transformed Kinships (MTK), measures that can indicate a subset would be beneficial for rare-trait discovery and genome-wide association scanning, respectively.

Implementation of spatial graph-theoretic genetic gravity models.
    The model framework is applicable for other types of spatial flow questions.
    Includes functions for constructing spatial graphs, sampling and summarizing
    associated raster variables and building unconstrained and singly constrained
    gravity models.

Provides tools for plotting gene clusters and transcripts by 
  importing data from GenBank, FASTA, and GFF files. It performs BLASTP and 
  MUMmer alignments [Altschul et al. (1990) <doi:10.1016/S0022-2836(05)80360-2>;
  Delcher et al. (1999) <doi:10.1093/nar/27.11.2369>] and displays results on 
  gene arrow maps. Extensive customization options are available, including 
  legends, labels, annotations, scales, colors, tooltips, and more.