MetaspotsByGroups bugfix (4c06c719) · Commits · github_fork / HdWGCNA

DESCRIPTION

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		Package: hdWGCNA
		Title: hdWGCNA
		Version: 0.2.00
		Version: 0.2.01
		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 0.2.01 (2022-10-06)
		## Added
		- None

		## Changes
		- Bugfix in `MetaspotsByGroups`.


		# hdWGCNA 0.2.00 (2022-09-23)
		## Added
		- `MetaspotsByGroups` to aggregate neighboring ST spots prior to network analysis.

+12 −0

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		@@ -96,6 +96,11 @@ ConstructMetaspots <- function(

		})

		if(length(tmp) <= 1){
		print('here')
		next
		}

		# get bc-neighbor results
		bcs <- unlist(lapply(1:length(tmp), function(k){tmp[[k]][[1]]}))
		cur_neighbors <- lapply(1:length(tmp), function(k){tmp[[k]][[2]]})
		@@ -119,8 +124,15 @@ ConstructMetaspots <- function(
		names(cur_neighbors) <- bcs

		# combine expression results
		if(length(tmp) <= 1){
		return(NULL)
		}
		agg_X <- do.call(rbind, lapply(1:length(tmp), function(k){tmp[[k]][[3]]}))


		# print(length(tmp))
		# print(dim(agg_X))

		# transpose expression matrix:
		agg_X <- t(agg_X)
		colnames(agg_X) <- bcs

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		@@ -8,6 +8,7 @@
		#' @param assay Assay to extract data for aggregation. Default = 'Spatial'
		#' @param slot Slot to extract data for aggregation. Default = 'counts'
		#' @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
		@@ -20,6 +21,7 @@ MetaspotsByGroups <- function(
		assay = 'Spatial',
		slot = 'counts',
		mode = 'sum',
		min_spots = 50,
		wgcna_name = NULL
		){

		@@ -76,6 +78,17 @@ MetaspotsByGroups <- function(
		groupings <- unique(seurat_obj$metacell_grouping)
		groupings <- groupings[order(groupings)]

		# remove groups that are too small:
		group_counts <- table(seurat_obj$metacell_grouping) < min_spots
		if(any(group_counts)){
		warning(paste0("Removing the following groups that did not meet min_spots: ", paste(names(group_counts)[group_counts], collapse=', ')))
		}
		groupings <- groupings[table(seurat_obj$metacell_grouping) >= min_spots]

		if(length(groupings) == 0 ){
		stop("No groups met the min_spots requirement.")
		}

		# split seurat obj by groupings
		seurat_list <- lapply(groupings, function(x){seurat_obj[,seurat_obj$metacell_grouping == x]})
		names(seurat_list) <- groupings

+3 −3

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		@@ -312,7 +312,7 @@ GetDatExpr <- function(seurat_obj, wgcna_name=NULL){
		#' @keywords scRNA-seq
		#' @export
		#' @examples
		#' SetDatExpr
		#' SetMultiExpr
		SetMultiExpr <- function(
		seurat_obj,
		group_name,
		@@ -348,9 +348,9 @@ SetMultiExpr <- function(

		# get the different groups present if not specified by the user:
		if(is.null(multi_groups)){
		multi_groups <- unique(seurat_obj@meta.data[[multi.group.by]])
		multi_groups <- unique(s_obj@meta.data[[multi.group.by]])
		} else{
		seurat_groups <- unique(seurat_obj@meta.data[[multi.group.by]])
		seurat_groups <- unique(s_obj@meta.data[[multi.group.by]])
		if(sum(multi_groups %in% seurat_groups) != length(multi_groups)){
		stop('Some or all groups specified in multi_groups not found in seurat_obj@meta.data[,multi.group.by]')
		}