f.clustABC.MultiSource: Consensus clustering from stacked ABC label matrices

In MosaiClusteR: An Umbrella Framework for Multi-Source and Multi-Omics Clustering

Consensus clustering from stacked ABC label matrices

Description

Turns a row-stacked matrix of per-iteration cluster labels (K \cdot R rows by N columns) into a co-clustering dissimilarity and applies cluster::agnes. S_{ij} is the co-clustering probability over iterations selecting both objects (B6). The co-clustering counts use the compiled C++ kernel count_coclustering_cpp (from src/mcpp_sampling.cpp) when available, otherwise a pure-R loop.

Usage

f.clustABC.MultiSource(
  res,
  numclust = NULL,
  dissimilarity = "mabc",
  linkage = "ward",
  alpha = 0.625,
  mds = FALSE
)

Arguments

res	Integer label matrix (0 = object not selected).
numclust	Optional number of clusters to cut the tree into.
dissimilarity	"mabc" (arc-cosine, default) or "abc" (linear).
linkage	AGNES agglomeration method.
alpha	Flexible-linkage parameter.
mds	Logical; draw an MDS of the dissimilarities.

Value

A list with DistM, Clust and (if numclust given) cut.

References

\insertCite

Amaratunga2008MosaiClusteR

See Also

M_ABC

MosaiClusteR documentation built on Oct. 25, 2026, 1:08 a.m.