clusterCellsInternal: Cluster cells and get similarity matrix of cells.

In PolinaPavlovich/CONCLUS: ScRNA-seq workflow CONCLUS - from CONsensus CLUSters to a meaningful CONCLUSion.

Description

The function returns consensus clusters by using hierarchical clustering on the similarity matrix of cells. It provides two options: to specify an exact number of clusters (with clusterNumber parameter) or to select the depth of splitting (deepSplit parameter).

Usage

clusterCellsInternal(dbscanMatrix, sceObject, clusterNumber = 0,
  deepSplit, cores = 14, clusteringMethod = "ward.D2")

Arguments

dbscanMatrix	an output matrix of conclus::runDBSCAN() function.
sceObject	a SingleCellExperiment object with your experiment.
clusterNumber	a parameter, specifying the exact number of cluster.
deepSplit	a parameter, specifying how deep we will split the clustering tree. It takes integers from 1 to 4.
cores	maximum number of jobs that CONCLUS can run in parallel.
clusteringMethod	a clustering methods passed to hclust() function.

Value

A SingleCellExperiment object with modified/created "clusters" column in the colData, and cells similarity matrix.

PolinaPavlovich/CONCLUS documentation built on May 10, 2019, 2:42 p.m.