compute_alternative_clustering: Compute alternative clustering at single-cell level

In mariiabilous/SuperCellBM:

Description

Compute alternative clustering at single-cell level

Usage

compute_alternative_clustering(
  sc.pca,
  N.comp = 10,
  N.clusters.seq = c(2:10),
  hclust_methods = c("ward.D", "ward.D2", "single", "complete", "average", "mcquitty",
    "median", "centroid"),
  other_clust_funcs = list(kmeans = kmeans),
  seed.seq = c(12346, 111, 19, 42, 7)
)

Arguments

sc.pca	PCA matrix or high dimensional matrix (cells as rows and coordinates/genes as columns)
N.comp	number or vector of PCs to use
N.clusters.seq	vector of number of clusters to compute
hclust_methods	a vector of method parameter form hclust
other_clust_funcs	list of ther clustering functions (in a format of kmeans)

Value

list of clusterings res in a format res[["number_of_clusters"]][["clustering_method[_random_seed]"]]

mariiabilous/SuperCellBM documentation built on Jan. 28, 2022, 7:45 p.m.