Bug fix for ModuleTraitCorrelation (a034f322) · Commits · github_fork / HdWGCNA

DESCRIPTION

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		Package: hdWGCNA
		Title: hdWGCNA
		Version: 0.1.1.9003
		Version: 0.1.1.9004
		Authors@R: c(
		person("Sam", "Morabito", , "smorabit@uci.edu", role = c("aut", "cre"),
		comment = c(ORCID = "0000-0002-7768-4856")),

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		# hdWGCNA 0.1.1.9004 (2022-6-13)
		## Added
		- None

		## Changes
		- Bug fix so `ModuleTraitCorrelation` can be run with a single trait.

		# hdWGCNA 0.1.1.9003 (2022-6-11)
		## Added
		- `GetHubGenes` function to extract the top hub genes from the module assignment table.

+39 −4

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		@@ -1776,6 +1776,12 @@ ModuleTraitCorrelation <- function(
		# get trait table:
		trait_df <- seurat_obj@meta.data[,traits]

		# cast vector to data frame if there's only one trait
		if(length(traits == 1)){
		trait_df <- data.frame(x = trait_df)
		colnames(trait_df) <- traits
		}

		# convert factors to numeric
		if(any(data_types == 'factor')){
		factor_traits <- traits[data_types == 'factor']
		@@ -1796,7 +1802,21 @@ ModuleTraitCorrelation <- function(

		# compute FDR:
		p_df <- cur_p %>%
		reshape2::melt() %>%
		reshape2::melt()

		if(length(traits) == 1){

		tmp <- rep(mods, length(traits))
		tmp <- factor(tmp, levels = mods)
		tmp <- tmp[order(tmp)]

		p_df$Var1 <- traits
		p_df$Var2 <- tmp
		rownames(p_df) <- 1:nrow(p_df)
		p_df <- dplyr::select(p_df, c(Var1, Var2, value))
		}

		p_df <- p_df %>%
		dplyr::mutate(fdr=p.adjust(value, method='fdr')) %>%
		dplyr::select(c(Var1, Var2, fdr))

		@@ -1839,7 +1859,22 @@ ModuleTraitCorrelation <- function(

		# compute FDR:
		p_df <- cur_p %>%
		reshape2::melt() %>%
		reshape2::melt()


		if(length(traits) == 1){

		tmp <- rep(mods, length(traits))
		tmp <- factor(tmp, levels = mods)
		tmp <- tmp[order(tmp)]

		p_df$Var1 <- traits
		p_df$Var2 <- tmp
		rownames(p_df) <- 1:nrow(p_df)
		p_df <- dplyr::select(p_df, c(Var1, Var2, value))
		}

		p_df <- p_df %>%
		dplyr::mutate(fdr=p.adjust(value, method='fdr')) %>%
		dplyr::select(c(Var1, Var2, fdr))

+2 −0

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		@@ -48,6 +48,7 @@ ConstructMetacells <- function(
		seurat_obj <- seurat_obj[,cells.use]
		}


		reduced_coordinates <- as.data.frame(seurat_obj@reductions[[reduction]]@cell.embeddings)
		nn_map <- FNN::knn.index(reduced_coordinates, k = (k - 1))
		row.names(nn_map) <- row.names(reduced_coordinates)
		@@ -132,6 +133,7 @@ ConstructMetacells <- function(
		max_shared = max_shared,
		mean_shared = mean_shared,
		median_shared = median_shared,
		density = density,
		n = ncol(new_exprs)
		)

+5 −2

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		@@ -1903,13 +1903,16 @@ PlotModuleTraitCorrelation <- function(

		if(is.null(wgcna_name)){wgcna_name <- seurat_obj@misc$active_wgcna}


		# get the module trait correlation results:
		temp <- GetModuleTraitCorrelation(seurat_obj)
		temp <- GetModuleTraitCorrelation(seurat_obj, wgcna_name)
		cor_list <- temp$cor
		pval_list <- temp$pval
		fdr_list <- temp$fdr

		if(is.null(dim(cor_list[[1]]))){
		stop('ModuleTraitCorrelation was run only for one trait. Heatmaps are not suggested for visualizing only one variable!')
		}

		# get module colors:
		modules <- GetModules(seurat_obj, wgcna_name)
		module_colors <- modules %>%