robustClusters,SummarizedExperiment-method {netSmooth} | R Documentation

## Perform robust clustering on dataset, and calculate the proportion of samples in robust clusters

### Description

Perform robust clustering on dataset, and calculate the proportion of samples in robust clusters

### Usage

    ## S4 method for signature 'SummarizedExperiment'
    robustClusters(x,
      dimReduceFlavor = "auto", is.counts = TRUE, ...)

    ## S4 method for signature 'matrix'
    robustClusters(x, ...)

### Arguments

`x` | matrix or SummarizedExperiment object
`dimReduceFlavor` | algorithm for dimensionality reduction step of clustering procedure. May be 'pca', 'tsne', 'dm', 'umap' or 'auto', which uses shannon entropy to pick the algorithm.
`is.counts` | logical: is the data counts
`...` | arguments passed on to 'clusterExperimentWorkflow'

### Value

list(clusters, proportion.robust)

### Examples

    data("smallscRNAseq")
    robustClusters(smallscRNAseq, dimReduceFlavor='pca')

[Package netSmooth version 1.6.0 Index]