clusterCellsInternal,scRNAseq-method {conclus} | R Documentation

## clusterCellsInternal

### Description

Returns consensus clusters by using hierarchical clustering on the similarity matrix of cells.

### Usage

    clusterCellsInternal(theObject, clusterNumber=0, deepSplit=4, cores=2,
                    clusteringMethod="ward.D2")

### Arguments

`theObject` | An Object of class scRNASeq for which the count matrix was normalized (see ?normaliseCountMatrix), tSNE were calculated (see ?generateTSNECoordinates), and dbScan was run (see ?runDBSCAN),
`clusterNumber` | Exact number of cluster. Default = 0 that will determine the number of clusters automatically.
`deepSplit` | Intuitive level of clustering depth. Options are 1, 2, 3, 4. Default = 4
`cores` | Maximum number of jobs that CONCLUS can run in parallel. Default is 1.
`clusteringMethod` | Clustering method passed to hclust() function. See ?hclust for a list of method. Default = "ward.D2".

### Value

An object of class scRNASeq with its cellsSimilarityMatrix and sceNorm slots updated.

### Author(s)

Ilyess RACHEDI, based on code by Polina PAVLOVICH and Nicolas DESCOSTES.

### See Also

plotCellSimilarity

### Examples

    ## Object containing the results of previous steps
    load(system.file("extdata/scrFull.Rdat", package="conclus"))

    ## Compute the cell similarity matrix
    scr <- clusterCellsInternal(scr, clusterNumber=4, cores=2)

[Package conclus version 1.0.0 Index]