ge_cluster  R Documentation 
Performs clustering for genotypes or tester environments based on a dissimilarity matrix.
ge_cluster( .data, env = NULL, gen = NULL, resp = NULL, table = FALSE, distmethod = "euclidean", clustmethod = "ward.D", scale = TRUE, cluster = "env", nclust = NULL )
.data 
The dataset containing the columns related to Environments, Genotypes
and the response variable. It is also possible to use a twoway table with genotypes
in lines and environments in columns as input. In this case you must use 
env 
The name of the column that contains the levels of the environments. Defaults to 
gen 
The name of the column that contains the levels of the genotypes. Defaults to 
resp 
The response variable(s). Defaults to 
table 
Logical values indicating if the input data is a twoway table with genotypes
in the rows and environments in the columns. Defaults to 
distmethod 
The distance measure to be used. This must be one of

clustmethod 
The agglomeration method to be used. This should be one
of 
scale 
Should the data be scaled befor computing the distances? Set to TRUE. Let Y_{ij} be the yield of Hybrid i in Location j, \bar Y_{.j} be the mean yield, and S_j be the standard deviation of Location j. The standardized yield (Zij) is computed as (Ouyang et al. 1995): Z_{ij} = (Y_{ij}  Y_{.j}) / S_j. 
cluster 
What should be clustered? Defaults to 
nclust 
The number of clust to be formed. Set to 
data The data that was used to compute the distances.
cutpoint The cutpoint of the dendrogram according to Mojena (1977).
distance The matrix with the distances.
de The distances in an object of class dist
.
hc The hierarchical clustering.
cophenetic The cophenetic correlation coefficient between distance matrix and cophenetic matrix
Sqt The total sum of squares.
tab A table with the clusters and similarity.
clusters The sum of square and the mean of the clusters for each
genotype (if cluster = "env"
or environment (if cluster = "gen"
).
labclust The labels of genotypes/environments within each cluster.
Tiago Olivoto tiagoolivoto@gmail.com
Mojena, R. 2015. Hierarchical grouping methods and stopping rules: an evaluation. Comput. J. 20:359363. doi: 10.1093/comjnl/20.4.359
Ouyang, Z., R.P. Mowers, A. Jensen, S. Wang, and S. Zheng. 1995. Cluster analysis for genotype x environment interaction with unbalanced data. Crop Sci. 35:13001305. doi: 10.2135/cropsci1995.0011183X003500050008x
library(metan) d1 < ge_cluster(data_ge, ENV, GEN, GY, nclust = 3) plot(d1, nclust = 3)
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