robustClusters,SummarizedExperiment-method {netSmooth} | R Documentation |
Perform robust clustering on dataset, and calculate the proportion of samples in robust clusters
## S4 method for signature 'SummarizedExperiment' robustClusters(x, dimReduceFlavor = "auto", is.counts = TRUE, ...) ## S4 method for signature 'matrix' robustClusters(x, ...)
x |
matrix or SummarizedExperiment object |
dimReduceFlavor |
algorithm for dimensionality reduction step of clustering procedure. May be 'pca', 'tsne', 'dm' or 'auto', which uses shannon entropy to pick the algorithm. |
is.counts |
logical: is the data counts |
... |
arguments passed on to 'clusterExperimentWorkflow' |
list(clusters, proportion.robust)
data("smallscRNAseq") robustClusters(smallscRNAseq, dimReduceFlavor='pca')