robustClusters: Perform robust clustering on dataset, and calculate the...

In netSmooth: Network smoothing for scRNAseq

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')

netSmooth documentation built on Nov. 8, 2020, 5:33 p.m.