clusterExperimentWorkflow {netSmooth} | R Documentation

## Performs clustering workflow using 'clusterExperiment' functions

### Description

Performs clustering workflow using 'clusterExperiment' functions

### Usage

    clusterExperimentWorkflow(se, dimReduceFlavor = c("pca", "tsne", "dm",
      "umap"), cluster.ks = 5:10, cluster.function = "pam",
      nVarDims = c(100, 500, 1000), makeConsensusProportion = 0.7,
      makeConsensusMinSize = 4, runMergeClusters = TRUE,
      is.counts = TRUE, random.seed = 1)

### Arguments

`se` | SummarizedExperiment object
`dimReduceFlavor` | algorithm for reduced dimension embedding step
`cluster.ks` | range of Ks to cluster over
`cluster.function` | clustering algorithm to use for all clusterings
`nVarDims` | numbers of variable genes to perform clusterings over
`makeConsensusProportion` | proportion of times samples need to be co-clustered for co-clustering step
`makeConsensusMinSize` | minimum cluster size
`runMergeClusters` | logical: merge similar clusters
`is.counts` | logical: is data counts
`random.seed` | passed to clusterExperiment. set to NULL in order to not set a random seed.

### Value

cluster assignments

[Package netSmooth version 1.6.0 Index]