onestep_clust: One round of clustering in the iteractive clustering pipeline

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

One round of clustering in the iteractive clustering pipeline

Description

One round of clustering in the iteractive clustering pipeline

Usage

onestep_clust(
  norm.dat,
  select.cells = colnames(norm.dat),
  counts = NULL,
  method = c("louvain", "leiden", "ward.D", "kmeans"),
  vg.padj.th = 0.5,
  dim.method = c("pca", "WGCNA"),
  max.dim = 20,
  rm.eigen = NULL,
  rm.th = 0.7,
  de.param = de_param(),
  merge.type = c("undirectional", "directional"),
  maxGenes = 3000,
  sampleSize = 4000,
  max.cl.size = 300,
  k.nn = 15,
  prefix = NULL,
  verbose = FALSE,
  regress.x = NULL
)

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. Default: columns of norm.dat
counts	Raw gene counts. Default NULL, inferred from norm.dat.
method	Clustering method. It can be "louvain", "hclust" and "kmeans". Default "louvain"
vg.padj.th	High variance gene adjusted pvalue cut off. Default 0.5.
dim.method	Dimension reduction techniques. Current options include "pca" and "WGCNA". Default "pca"
max.dim	The number of top dimensions retained. Default 20. Since clustering is performed iteratively, not all relevant dimensions need to be captured in one iterations.
rm.eigen	The reduced dimensions that need to be masked and removed. Default NULL.
rm.th	The cutoff for correlation between reduced dimensions and rm.eigen. Reduced dimensions with correlatin with any rm.eigen vectors are not used for clustering. Default 0.7
de.param	The differential gene expression threshold. See de_param() function for details.
maxGenes	Only used when dim.method=="WGCNA". The maximum number of genes to calculate gene modules.
sampleSize	The number of sampled cells to compute reduced dimensions.
max.cl.size	Sampled cluster size. This is to speed up limma DE gene calculation. Instead of using all cells, we randomly sampled max.cl.size number of cells for testing DE genes.
prefix	Used to keep track of intermediate results in "verbose" mode. Default NULL.
verbose	Default FALSE
type	Can either be "undirectional" or "directional". If "undirectional", the differential gene threshold de.param is applied to combined up-regulated and down-regulated genes, if "directional", then the differential gene threshold is applied to both up-regulated and down-regulated genes.

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.