scoexp: SCoexp module

In navinlabcode/CellTrek: Spatial Charting of Single Cell Transcriptomes in Tissues

SCoexp module

Description

SCoexp module

Usage

scoexp(
  celltrek_inp,
  sigm = NULL,
  assay = "RNA",
  gene_select = NULL,
  zero_cutoff = 5,
  cor_method = "spearman",
  approach = c("cc", "wgcna")[1],
  maxK = 8,
  k = 8,
  avg_con_min = 0.5,
  avg_cor_min = 0.5,
  min_gen = 20,
  max_gen = 100,
  keep_cc = T,
  keep_wgcna = T,
  keep_kern = T,
  keep_wcor = T,
  ...
)

Arguments

celltrek_inp	CellTrek input on cell of interests
approach	Which approach to use? consensus clustering (cc) or weighted correlation network analysis (wgcna)
keep_cc	If TRUE, keep the cc model
keep_wgcna	If TRUE, keep the wgcna model
...

Examples

scoexp(celltrek_inp, sigm=NULL, assay='RNA', gene_select=NULL, zero_cutoff=5, cor_method='spearman', approach=c('cc', 'wgcna')[1], maxK=8, k=8, avg_con_min=.5, avg_cor_min=.5, min_gen=20, max_gen=100, keep_cc=T, keep_wgcna=T, keep_kern=T, keep_wcor=T)

navinlabcode/CellTrek documentation built on April 15, 2022, 8:04 a.m.