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‎NAMESPACE‎

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@@ -41,6 +41,7 @@ import(ggExtra)
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import(ggalluvial)
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import(ggplot2)
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import(ggrepel)
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import(grDevices)
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import(iterators)
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import(methods)
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import(parallel)

‎R/methods.R‎

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@@ -806,10 +806,10 @@ get_lr_path <- function(object, celltype_sender, celltype_receiver, ligand, rece
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ggi_tf <- unique(pathways[, c("src", "dest", "src_tf", "dest_tf")])
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st_data <- .get_st_data(object)
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st_meta <- .get_st_meta(object)
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if (!celltype_sender %in% colnames(object@coef)) {
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if (!celltype_sender %in% st_meta$celltype) {
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stop("Please provide the correct name of celltype_sender!")
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}
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if (!celltype_receiver %in% colnames(object@coef)) {
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if (!celltype_receiver %in% st_meta$celltype) {
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stop("Please provide the correct name of celltype_receiver!")
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}
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if (!ligand %in% rownames(st_data)) {

‎R/plot.R‎

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@@ -571,13 +571,15 @@ plot_ccdist <- function(object, celltype_sender, celltype_receiver, color = NULL
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#' @param type Set 'sig' to plot significant LR pairs or set 'number' to plot the number of spatial LR interactions.
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#' @param fontsize_number fontsize of the numbers displayed in cells.
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#' @param number_color color of the text.
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#' @import ggplot2 pheatmap
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#' @param color_low For 'number' type, define the color for the lowest value.
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#' @param color_high For 'number' type, define the color for the highest value.
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#' @import ggplot2 pheatmap grDevices
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#' @importFrom ggpubr get_palette
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#' @importFrom reshape2 dcast
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#' @export
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579-
plot_cci_lrpairs <- function(object, celltype_sender, celltype_receiver, top_lrpairs = 20, color = NULL,
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border_color = "black", type = NULL, fontsize_number = 1, number_color = "black") {
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plot_cci_lrpairs <- function(object, celltype_sender, celltype_receiver, top_lrpairs = 20, color = NULL, border_color = "black", type = "sig",
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fontsize_number = 5, number_color = "black", color_low = NULL, color_high = NULL) {
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# check
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if (!is(object, "SpaTalk")) {
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stop("Invalid class for object: must be 'SpaTalk'!")
@@ -624,25 +626,41 @@ plot_cci_lrpairs <- function(object, celltype_sender, celltype_receiver, top_lrp
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}
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ligand <- unique(lrpair$ligand)
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receptor <- unique(lrpair$receptor)
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# get lrpair_real
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lrpair_real <- object@lr_path$lrpairs
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lrpair_real <- lrpair_real[, c(1, 2)]
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lrpair_real$score <- 1
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lrpair_mat <- reshape2::dcast(lrpair_real, formula = ligand ~ receptor, fill = 0, value.var = "score")
632-
rownames(lrpair_mat) <- lrpair_mat$ligand
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lrpair_mat <- lrpair_mat[, -1]
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lrpair_mat <- lrpair_mat[ligand, receptor]
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if (!is.data.frame(lrpair_mat)) {
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stop("Limited number of ligand-receptor interactions!")
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}
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plot_res <- matrix("", nrow = length(ligand), ncol = length(receptor))
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rownames(plot_res) <- ligand
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colnames(plot_res) <- receptor
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for (i in 1:nrow(lrpair)) {
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plot_res[lrpair$ligand[i], lrpair$receptor[i]] <- "*"
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}
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pheatmap::pheatmap(lrpair_mat, cluster_cols = F, cluster_rows = F, color = heat_col, border_color = border_color,
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legend = F, display_numbers = plot_res, fontsize_number = fontsize_number, number_color = number_color)
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if (type == "sig") {
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# get lrpair_real
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lrpair_real <- object@lr_path$lrpairs
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lrpair_real <- lrpair_real[, c(1, 2)]
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lrpair_real$score <- 1
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lrpair_mat <- reshape2::dcast(lrpair_real, formula = ligand ~ receptor, fill = 0, value.var = "score")
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rownames(lrpair_mat) <- lrpair_mat$ligand
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lrpair_mat <- lrpair_mat[, -1]
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lrpair_mat <- lrpair_mat[ligand, receptor]
638+
if (!is.data.frame(lrpair_mat)) {
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stop("Limited number of ligand-receptor interactions!")
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}
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plot_res <- matrix("", nrow = length(ligand), ncol = length(receptor))
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rownames(plot_res) <- ligand
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colnames(plot_res) <- receptor
644+
for (i in 1:nrow(lrpair)) {
645+
plot_res[lrpair$ligand[i], lrpair$receptor[i]] <- "*"
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}
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pheatmap::pheatmap(lrpair_mat, cluster_cols = F, cluster_rows = F, color = heat_col, border_color = border_color, legend = F, display_numbers = plot_res,
648+
fontsize_number = fontsize_number, number_color = number_color, main = "Significantly enriched LRI")
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} else {
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if (is.null(color_low)) {
651+
color_low <- "orange"
652+
}
653+
if (is.null(color_high)) {
654+
color_high <- "red"
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}
656+
lrpair_real <- lrpair[,c("ligand","receptor","lr_co_exp_num")]
657+
lrpair_mat <- reshape2::dcast(lrpair_real, formula = ligand ~ receptor, fill = 0, value.var = "lr_co_exp_num")
658+
rownames(lrpair_mat) <- lrpair_mat$ligand
659+
lrpair_mat <- lrpair_mat[, -1]
660+
heat_color <- grDevices::colorRampPalette(c(color_low, color_high))(max(as.matrix(lrpair_mat))-1)
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heat_color <- c("white", heat_color)
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pheatmap::pheatmap(lrpair_mat, cluster_cols = F, cluster_rows = F, border_color = border_color, color = heat_color, main = "Number of spatial LRIs")
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}
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}
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#' @title Plot LR pair

‎man/plot_cci_lrpairs.Rd‎

Lines changed: 9 additions & 3 deletions
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‎script/cellchat.R‎

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#==============================================
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#================== CellChat ==================
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#==============================================
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library(CellChat)
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library(SpaTalk)
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library(tidyverse)
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library(Seurat)
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options(stringsAsFactors = FALSE)
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load(paste0(system.file(package = 'SpaTalk'),'/extdata/starmap_data.rda')) # starmap_data
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load(paste0(system.file(package = 'SpaTalk'),'/extdata/starmap_meta.rda')) # starmap_meta
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ndata <- starmap_data
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celltype <- starmap_meta
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rownames(celltype) <- celltype$cell
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all(colnames(ndata) == celltype$cell)
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seuratObj <- CreateSeuratObject(counts = ndata)
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seuratObj <- NormalizeData(seuratObj)
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Idents(seuratObj) <- celltype$celltype
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data.input <- GetAssayData(seuratObj, assay = "RNA", slot = "data") # normalized data matrix
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labels <- Idents(seuratObj)
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meta <- data.frame(labels = labels, row.names = names(labels)) # create a dataframe of the cell labels
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cellchat <- createCellChat(object = data.input, meta = meta, group.by = "labels")
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CellChatDB <- CellChat::CellChatDB.mouse
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cellchat@DB <- CellChatDB
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cellchat <- subsetData(cellchat)
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future::plan("multisession", workers = 4) # do parallel
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cellchat <- identifyOverExpressedGenes(cellchat)
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cellchat <- identifyOverExpressedInteractions(cellchat)
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cellchat <- computeCommunProb(cellchat)
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cellchat <- filterCommunication(cellchat, min.cells = 10)
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df.net <- res_cellchat[[use_db]][['starmap']][['starmap']] <- df.net %>% dplyr::select(1:6)

‎script/cellphonedb.sh‎

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#-----------------------------------
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#--- R script after
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#-----------------------------------
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# Run before python
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library(SpaTalk)
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library(tidyverse)
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load(paste0(system.file(package = 'SpaTalk'),'/extdata/starmap_data.rda')) # starmap_data
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load(paste0(system.file(package = 'SpaTalk'),'/extdata/starmap_meta.rda')) # starmap_meta
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# orthologs gene
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ndata <- starmap_data
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orthologs_gene <- mapper[rownames(ndata)]
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na_gene <- rownames(ndata)[is.na(orthologs_gene)]
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ndata <- ndata[!is.na(orthologs_gene),]
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rownames(ndata) <- orthologs_gene[!is.na(orthologs_gene)] %>% make.names()
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18+
celltype <- starmap_meta
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rownames(celltype) <- celltype$cell
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all(colnames(ndata) == celltype$cell)
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# create Seurat object
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seuratObj <- CreateSeuratObject(counts = ndata)
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Idents(seuratObj) <- celltype$celltype
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seuratObj[['celltype']] <- celltype$celltype
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seuratObj <- NormalizeData(seuratObj)
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29+
writeMM(seuratObj@assays$RNA@counts, file = 'data/cpdb_input/starmap_counts_mtx/matrix.mtx')
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# save gene and cell names
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write(x = rownames(seuratObj@assays$RNA@counts), file = "data/cpdb_input/starmap_counts_mtx/features.tsv")
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write(x = colnames(seuratObj@assays$RNA@counts), file = "data/cpdb_input/starmap_counts_mtx/barcodes.tsv")
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[email protected]$Cell = rownames([email protected])
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df = [email protected][, c('Cell', 'celltype')]
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write.table(df, file ='data/cpdb_input/starmap_meta.tsv', sep = '\t', quote = F, row.names = F)
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#===============================================================================================
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#-----------------------------------
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#--- python script after
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#-----------------------------------
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conda activate cpdb
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cd data/cpdb_input/
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cellphonedb method statistical_analysis starmap_meta.tsv starmap_counts_mtx/ --counts-data gene_name
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#-----------------------------------
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#--- python script before
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#-----------------------------------
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#=================================================================================
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#-----------------------------------
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#--- R script after
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#-----------------------------------
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# standardize cpdb output
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res_cpdb_uniondb <- list()
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# create mapper to convert gene into mouse gene
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mapper <- gene2orthologs$mousegene
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names(mapper) <- gene2orthologs$humangene
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gene2orthologs <- readRDS("~/待处理/Spatalk_Benchmark/verified_database/cpdb/gene2orthologs_human_mouse.rds")
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cpdb2df <- function(data) {
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df_data <- data.frame()
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Ligand = c()
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Receptor = c()
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Ligand.Cluster = c()
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Receptor.Cluster = c()
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isReceptor_fst = c()
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isReceptor_scn = c()
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MeanLR = c()
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for (i in 1:nrow(data)) {
78+
pair <- strsplit(data$`interacting_pair`[i],split = "_")
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for (j in 13:ncol(data)) {
80+
c_pair = strsplit(colnames(data)[j],"\\|")
81+
if (data[i,j] != 0.0) {
82+
Ligand <- c(Ligand,pair[[1]][1])
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Receptor <- c(Receptor,pair[[1]][2])
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Ligand.Cluster <- c(Ligand.Cluster,c_pair[[1]][1])
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Receptor.Cluster <- c(Receptor.Cluster,c_pair[[1]][2])
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isReceptor_fst <- c(isReceptor_fst,data$`receptor_a`[i])
87+
isReceptor_scn <- c(isReceptor_scn,data$`receptor_b`[i])
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MeanLR <- c(MeanLR,data[i,j])
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}
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}
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}
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df_data <- data.frame(Ligand = Ligand, Receptor = Receptor,
95+
Ligand.Cluster = Ligand.Cluster,Receptor.Cluster = Receptor.Cluster,
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isReceptor_fst = isReceptor_fst,
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isReceptor_scn = isReceptor_scn,
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MeanLR = MeanLR)
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return(df_data)
100+
}
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#--- starmap
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cpdb_O <- read.table(paste0("cpdb_input/","/out/significant_means.txt"),sep = "\t",header = T,check.names = F,stringsAsFactors = F)
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cpdb_O[is.na(cpdb_O)] <- 0
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cpdb_O <- cpdb2df(cpdb_O)
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cpdb_O <- cpdb_O %>% mutate(Ligand = mapper[Ligand], Receptor = mapper[Receptor])
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cpdb_O <- cpdb_O %>% rename(receptor = Ligand,ligand = Receptor, sender = Receptor.Cluster, receiver = Ligand.Cluster)
109+

‎vignettes/SpaTalk.pdf‎

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