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Cluster genotypes or environments in R
library(metan)
View(data_ge)
The distance measure to be used
euclidean 'maximum' 'manhattan', 'canberra', 'binary', or 'minkowski'
d1 =ge_cluster(data_ge, ENV, GEN,GY, nclust = 3,distmethod='euclidean',clustmethod='ward.D',
scale = TRUE,cluster="env")
The agglomeration method to be used.
#'ward.D' (Default), 'ward.D2', 'single', 'complete',
#''average' (= UPGMA), 'mcquitty' (= WPGMA), 'median' (= WPGMC) or 'centroid' (= UPGMC).
plot(d1, nclust =2)
d1$hc # The hierarchical clustering.
d1$tab # A table with the clusters and similarity.
d1$clusters # The sum of square and the mean of the clusters for each genotype
d1$labclust#The labels of genotypes/environments within each cluster.
d1$data # The data that was used to compute the distances
d1$cutpoint # The cutpoint of the dendrogram according to Mojena (1977).
d1$distance # The matrix with the distances
d1$Sqt # The total sum of squares.
d1$cophenetic # The cophenetic correlation coefficient between distance matrix and cophenetic matrix