cluster_exposure: Perform clustering analysis from a musica result object

In campbio/musicatk: Mutational Signature Comprehensive Analysis Toolkit

Perform clustering analysis from a musica result object

Description

Proportional sample exposures will be used as input to perform clustering.

Usage

cluster_exposure(
  result,
  nclust,
  proportional = TRUE,
  method = "kmeans",
  dis.method = "euclidean",
  hc.method = "ward.D",
  clara.samples = 5,
  iter.max = 10,
  tol = 1e-15
)

Arguments

result	A musica_result object generated by a mutational discovery or prediction tool.
nclust	Pre-defined number of clusters.
proportional	Logical, indicating if proportional exposure (default) will be used for clustering.
method	Clustering algorithms. Options are "kmeans" (K-means), "hkmeans" (hybrid of hierarchical K-means), "hclust" (hierarchical clustering), "pam" (PAM), and "clara" (Clara).
dis.method	Methods to calculate dissimilarity matrix. Options are "euclidean" (default), "manhattan", "jaccard", "cosine", and "canberra".
hc.method	Methods to perform hierarchical clustering. Options are "ward.D" (default), "ward.D2", "single", "complete", "average", "mcquitty", "median", and "centroid".
clara.samples	Number of samples to be drawn from dataset. Only used when "clara" is selected. Default is 5.
iter.max	Maximum number of iterations for k-means clustering.
tol	Tolerance level for kmeans clustering level iterations

Value

A one-column data frame with sample IDs as row names and cluster number for each sample.

See Also

kmeans

Examples

set.seed(123)
data(res_annot)
clust_out <- cluster_exposure(res_annot, nclust = 2)

campbio/musicatk documentation built on July 14, 2024, 8:28 a.m.