iter_consensus_clust: Iterative consensus clustering

Description Usage Arguments Value

View source: R/consensusCluster.R

Description

Iterative consensus clustering

Usage

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iter_consensus_clust(co.ratio, cl.list, norm.dat,
  select.cells = colnames(co.ratio), all.col = NULL, diff.th = 0.25,
  prefix = NULL, method = c("auto", "louvain", "ward.D"), verbose = FALSE,
  de.param = de.param, result = NULL, rd.dat = NULL)

Arguments

co.ratio

cell cell co-clustering matrix

cl.list

The list of subsampled clustering results.

norm.dat

The log2 transformed normalzied expression matrix

select.cells

Cells to be clustered

all.col

Color bars for plotting heatmap. Default NULL

diff.th

The difference of co-clustering probablities for splitting a cluster.

prefix

Default NULL.

method

Clustering methods. Default "auto"

verbose

Default FALSE

result

Pre-computed clustering results used for further splitting. Default NULL.

min.cells

Minimal number of cells in a cluster. Default 4

...

Other parameters passed to merge_cl

Value

A list with cluster membership, and top pairwise marker genes.


AllenInstitute/scrattch.hicat documentation built on Nov. 6, 2018, 9:47 p.m.