iter_clust: Iterative clustering algorithm for single cell RNAseq dataset

Description Usage Arguments Value Examples

View source: R/cluster.R

Description

Iterative clustering algorithm for single cell RNAseq dataset

Usage

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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

Examples

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clust.result <- iter_clust(norm.dat)
          clust.result <- iter_clust(norm.dat, de.param = de_param(q1.th = 0.5, de.score.th = 100))

AllenInstitute/scrattch.hicat documentation built on May 5, 2019, 1:32 a.m.