clusterExperimentWorkflow {netSmooth} | R Documentation |
Performs clustering workflow using 'clusterExperiment' functions
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)
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. |
cluster assignments