GroupProj: 'GroupProj' of SelectVar object
In kimod: A k-tables approach to integrate multiple Omics-Data

Description Usage Arguments Value Author(s) Examples

This function calculates the relashionship between genes and samples from SelectVar method. Also, computes agglomerative hierarchical clustering of the dataset.

GroupProj(object, NGroups = 2, metric = c("euclidean", "manhattan"),
  method = c("ward", "single", "complete", "weighted", "flexible"), ...)

## S4 method for signature 'SelectVar'
GroupProj(object, NGroups = 2, metric = c("euclidean",
  "manhattan"), method = c("ward", "single", "complete", "weighted",
  "flexible"), ...)

`object`	it is an object of SelectVar Class.
`NGroups`	An integer scalar or vector with the desired number of clusters.
`metric`	The character string specifying the metric to be used to calculate dissimilarities between observations. The currently available options are "euclidean" and "manhattan". Euclidean distances are root sum-of-squares of differences, and manhattan distances are the sum of absolute differences.
`method`	character string defining the clustering method. The methods implemented are "average" ([unweighted pair-] group [arithMetic] average method, aka b "single" (single linkage), "complete" (complete linkage), "ward" (Ward's method), "weighted" (weighted average linkage, aka b its generalization "flexible" which uses (a constant version of) the Lance-Williams formula and the par.method argument, and "gaverage" a generalized "average" aka b also using the Lance-Williams formula and par.method. (See `agnes`).
`...`	Additional parameters for `agnes`.

GroupProj

GroupProj with the corresponding completed slots

M L Zingaretti, J A Demey-Zambrano, J L Vicente Villardon, J R Demey

{
data(NCI60Selec)
Z1<-DiStatis(NCI60Selec)
M1<-SelectVar(Z1,Crit="R2-Adj")
A1<-GroupProj(M1,method="ward",metric="euclidean",NGroups=6)
data(winesassesors)
Z2<-DiStatis(winesassesors)
M2<-SelectVar(Z2,Crit="R2-Adj")
A2<-GroupProj(M2,method="ward",metric="euclidean",NGroups=6)
}