adding in functinos that accidently got removed (73b8c7df) · Commits · github_fork / HdWGCNA

NAMESPACE

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		# Generated by roxygen2: do not edit by hand

		export(AvgModuleExpr)
		export(ComputeModuleEigengene)
		export(ConstructMetacells)
		export(ConstructMetaspots)
		export(ConstructNetwork)
		export(DimPlotMetacells)
		export(DoHubGeneHeatmap)
		export(EnrichrBarPlot)
		@@ -39,8 +41,11 @@ export(GetWGCNAParams)
		export(HubGeneNetworkPlot)
		export(MetacellsByGroups)
		export(MetaspotsByGroups)
		export(ModuleConnectivity)
		export(ModuleCorrNetwork)
		export(ModuleCorrelogram)
		export(ModuleEigengenes)
		export(ModuleExprScore)
		export(ModuleFeaturePlot)
		export(ModuleNetworkPlot)
		export(ModulePreservation)
		@@ -63,6 +68,7 @@ export(PlotModuleTraitCorrelation)
		export(PlotSoftPowers)
		export(ProjectModules)
		export(ROCCurves)
		export(ReassignModules)
		export(ResetModuleColors)
		export(ResetModuleNames)
		export(RunEnrichr)

+1 −0

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		@@ -35,6 +35,7 @@
		#'
		#' @import WGCNA
		#' @import Seurat
		#' @export
		ConstructNetwork <- function(
		seurat_obj, soft_power=NULL, min_power=3,
		tom_outdir="TOM",

+0 −6

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		@@ -7,10 +7,7 @@
		#' @param mode "sum" or "average"
		#' @param assay Assay to extract data for aggregation. Default = 'Spatial'
		#' @param slot Slot to extract data for aggregation. Default = 'counts'
		#' @keywords ST
		#' @export
		#' @examples
		#'
		ConstructMetaspots <- function(
		cur_seurat,
		mode = 'sum',
		@@ -199,10 +196,7 @@ ConstructMetaspots <- function(
		#' @param mode determines how to make gene expression profiles for metacells from their constituent single cells. Options are "average" or "sum".
		#' @param min_spots the minimum number of spots in a particular grouping to construct metaspots
		#' @param wgcna_name name of the WGCNA experiment
		#' @keywords ST
		#' @export
		#' @examples
		#'
		MetaspotsByGroups <- function(
		seurat_obj,
		group.by=c('seurat_clusters'),

+1 −0

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		@@ -36,6 +36,7 @@
		#'
		#' @import WGCNA
		#' @import Seurat
		#' @export
		ModuleConnectivity <- function(
		seurat_obj,
		group.by = NULL,

+3 −3

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		@@ -12,6 +12,7 @@
		#' @param pc_dim Which PC to use as the module eigengene? Default to 1.
		#' @param assay Assay in seurat_obj to compute module eigengenes. Default is DefaultAssay(seurat_obj)
		#' @param wgcna_name name of the WGCNA experiment
		#' @export
		ComputeModuleEigengene <- function(
		seurat_obj,
		cur_mod,
		@@ -167,6 +168,7 @@ ComputeModuleEigengene <- function(
		#' or other factors using the Harmony algorithm with the group.by.vars parameter.
		#'
		#' @import Seurat
		#' @export
		ModuleEigengenes <- function(
		seurat_obj,
		group.by.vars=NULL,
		@@ -313,6 +315,7 @@ ModuleEigengenes <- function(
		#' the expression level of each module. The user can choose between Seurat AddModuleScore
		#' or UCell using the method parameter.
		#'
		#' @export
		ModuleExprScore <- function(
		seurat_obj,
		n_genes = 25,
		@@ -379,10 +382,7 @@ ModuleExprScore <- function(
		#' Computes module eigengenes for all WGCNA co-expression modules
		#'
		#' @param seurat_obj A Seurat object
		#' @keywords scRNA-seq
		#' @export
		#' @examples
		#' AverageModuleExpr (pbmc)
		AvgModuleExpr <- function(seurat_obj, n_genes = 25, wgcna_name=NULL, ...){

		# set as active assay if wgcna_name is not given