clusterCells: Perform clustering analysis on the samples in the expression...

In joeburns06/hocuspocus: A Suite of Single-Cell RNA-Seq Analysis Tools Built for Dummy Biologists

Description

Takes ExpressionSet object and clusters the samples using hierarchical, k-means, or pam clustering.

Usage

clusterCells(cellData, k = 3, methods = c("hierarchical", "kmeans", "pam"),
  hier_dist = "euclidean", hier_clust = "ward")

Arguments

cellData	ExpressionSet object created with readCells (and preferably transformed with prepCells). It is also helpful to first run reduceGenes_var and reduceGenes_pca.
k	The number of desired clusters into which the samples are to be grouped. The function calcGap can be used to obtain an unbiased estimate of the number of clusters.
methods	Vector of character strings specifying which of the three clustering methods to perform. All three can be specified, or a subset of the three.
hier_dist	Character string specifying how to compute the distance matrix for 'hierarchical.' Equivalent to the 'method' parameter within the dist function.
hier_clust	Character string specifying the clustering method for 'hierarchical.' Equivalent to the 'method' parameter within the hclust function.

Value

For each clustering method specified, a column is added to pData containing the cluster information for each sample (clusters are designated by roman numerals).

joeburns06/hocuspocus documentation built on May 19, 2019, 2:59 p.m.