splitTrainClusters {MetaNeighbor}R Documentation

Split train clusters according to AUROC similarity to test clusters.

Description

This function computes hierarchical clustering to group similar train clusters, using similarity to test clusters as features, then uses a standard tree cutting algorithm to obtain groups of similar clusters. Note that the cluster hierarchy corresponds exactly to the column dendrogram shown when using the plotHeatmapPretrained function.

Usage

splitTrainClusters(mn_scores, k)

Arguments

mn_scores

An AUROC matrix as generated by MetaNeighborUS, usually with the "trained_model" option.

k

The number of desired cluster sets.

Value

A list of cluster sets, each cluster set is a character vector containg cluster labels.

See Also

plotHeatmapPretrained


[Package MetaNeighbor version 1.10.0 Index]