iclust: iCellR Clustering

In rezakj/iCellR: Analyzing High-Throughput Single Cell Sequencing Data

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",
  sensitivity = 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".
sensitivity	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.

rezakj/iCellR documentation built on March 29, 2024, 6:55 p.m.