working on tutorials (fa9d7d44) · Commits · github_fork / HdWGCNA

R/WGCNA_functions.R

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		@@ -113,7 +113,9 @@ SelectNetworkGenes <- function(
		#' SetupForWGCNA(pbmc)
		SetupForWGCNA <- function(
		seurat_obj, wgcna_name,
		group=NULL, features = NULL,...){
		group=NULL, features = NULL,
		...
		){

		# set the active WGCNA variable
		seurat_obj <- SetActiveWGCNA(seurat_obj, wgcna_name)

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		@@ -98,7 +98,7 @@ GetWGCNAGenes <- function(seurat_obj, wgcna_name=NULL){
		###########################


		#' SetDatExpr
		#' spr
		#'
		#' This function sets up the expression matrix from the metacell object.
		#'

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		# scWGCNA <img src="man/figures/logo_v2.png" align="right" height="20%" width="20%" />
		# scWGCNA <img src="man/figures/logo.png" align="right" height="20%" width="20%" />

		scWGCNA is an R package for performing [weighted gene co-expression network analysis (WGCNA)](https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/) in single-cell
		RNA-seq data. scWGCNA constructs co-expression networks in a cell-type-specific manner,

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		@@ -19,6 +19,27 @@ articles:
		navbar: ~
		contents:
		- basic_tutorial
		- title: Network Visualization
		navbar: ~
		contents:
		- network_visualizations
		- title: Enrichment Analysis
		navbar: ~
		contents:
		- enrichment_analysis
		- title: Module Trait Correlation
		navbar: ~
		contents:
		- module_trait_correlation
		- title: Projecting Modules
		navbar: ~
		contents:
		- projecting_modules
		- title: Motif Analysis
		navbar: ~
		contents:
		- motif_analysis


		reference:
		- title: Metacells

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