iCellR (version 1.5.1)

iclust: iCellR Clustering

Description

This function takes an object of class iCellR and finds optimal number of clusters and clusters the data.

Usage

iclust(
  x = NULL,
  dist.method = "euclidean",
  k = 100,
  data.type = "pca",
  dims = 1:10,
  return.graph = FALSE
)

Arguments

x

An object of class iCellR.

dist.method

the distance measure to be used to compute the dissimilarity matrix. This must be one of: "euclidean", "maximum", "mandatattan", "canberra", "binary", "minkowski" or "NULL". By default, distance="euclidean". If the distance is "NULL", the dissimilarity matrix (diss) should be given by the user. If distance is not "NULL", the dissimilarity matrix should be "NULL".

k

KNN the higher the number the less sensitivity, default = 100.

data.type

Choose between "tsne", "pca", "umap", default = "pca".

dims

PCA dimentions to be use for clustering, default = 1:10.

return.graph

return igraph object, default = FALSE.

Value

An object of class iCellR.