iter_clust: Iterative clustering algorithm for single cell RNAseq dataset

In AllenInstitute/scrattch.hicat: Hierarchical Iterative Clustering Analysis for Transcriptomic data

Iterative clustering algorithm for single cell RNAseq dataset

Description

Iterative clustering algorithm for single cell RNAseq dataset

Usage

iter_clust(
  norm.dat,
  select.cells = colnames(norm.dat),
  prefix = NULL,
  split.size = 10,
  result = NULL,
  method = "auto",
  ...
)

Arguments

norm.dat	normalized expression data matrix in log transform, using genes as rows, and cells and columns. Users can use log2(FPKM+1) or log2(CPM+1)
select.cells	The cells to be clustered
prefix	The character string to indicate current iteration.
split.size	The minimal cluster size for further splitting
result	The current clustering result as basis for further splitting.
method	Clustering method. It can be "auto", "louvain", "hclust"
...	Other parameters passed to method 'onestep_clust()'

Value

Clustering result is returned as a list with two elements: cl: cluster membership for each cell markers: top markers that seperate clusters

AllenInstitute/scrattch.hicat documentation built on June 6, 2024, 5:31 a.m.