escogcn: Compute the gene co-expression network

In JINJINT/splattermodify: Simple Simulation of Single-cell RNA Sequencing Data

Description

compute the gene co-expression netowrk using different correlation metric

Usage

gcn(count, genes = NULL, CPM = TRUE, CPM2 = FALSE,
  name = "pearson")

Arguments

count	a gene by cell matrix containing the expression count.
genes	a vector of names of selected genes, default is NULL, indicating choosing all the genes.
CPM	whether to use Counts Per Millon normalization on the whole data sets or not.
CPM2	whether to use Counts Per Millon normalization on the selected genes or not.
name	a string indicating what type of correlation metric ("pearson", "spearman", "kendall","cosine") to use, default options is "pearson".

Value

a correlation matrix

Examples

data = matrix(rnorm(100),20,5)
gcndata = gcn(data)

JINJINT/splattermodify documentation built on May 19, 2021, 4:05 p.m.