upload helper functions

src/helpers/utils.R

@@ -0,0 +1,71 @@
+# spatial autocorrelation
+generate_moransI <- function(adata){
+  sp_count <- adata$layers[["logcounts"]]
+
+  W <- cbind.data.frame(row = as.numeric(sapply(strsplit(rownames(sp_count),split="x"),"[",1)),
+                        col = as.numeric(sapply(strsplit(rownames(sp_count),split="x"),"[",2)))
+  W <- 1/as.matrix(dist(W))
+  diag(W) <- 0
+  res <- spots::BivariateMoransI( X =  sp_count , W =  W)
+  return(res$Morans.I)
+}
+
+# Spatial varianble gene
+generate_svg_sparkx <- function(adata) {
+  sp_count <- Matrix::t(adata$layers[["counts"]])
+
+  info <- cbind.data.frame(x=as.numeric(sapply(strsplit(colnames(sp_count),split="x"),"[",1)),
+                          y=as.numeric(sapply(strsplit(colnames(sp_count),split="x"),"[",2)))
+
+  rownames(info) <- colnames(sp_count)
+
+  location <- as.matrix(info)
+  mt_idx <- grep("mt-", rownames(sp_count))
+  if (length(mt_idx) != 0) {
+    sp_count <- sp_count[-mt_idx, ]
+  }
+  sparkX <- SPARK::sparkx(sp_count, location, numCores = 1, option = "mixture")
+  return(sparkX)
+}
+
+# cell type deconvolution
+CARD_processing <- function(sp_adata, sc_adata){
+  sp_adata <- input_real_sp
+  sc_adata <- input_sc
+  spatial_count <- Matrix::t(sp_adata$layers[["counts"]])
+  spatial_location <- cbind.data.frame(
+    x = as.numeric(sapply(strsplit(colnames(spatial_count),split="x"),"[",1)),
+    y = as.numeric(sapply(strsplit(colnames(spatial_count),split="x"),"[",2)))
+  # names(spatial_location) <- c("x", "y")
+  sc_count <- Matrix::t(sc_adata$layers[["counts"]])
+  sc_meta <- cbind.data.frame(
+    cellID = rownames(sc_adata),
+    cellType = input_sc$obs$cell_type,
+    sampleInfo = input_sc$obs$donor_id
+  )
+  rownames(sc_meta) <- sc_meta$cellID
+  rownames(spatial_location) <- colnames(spatial_count)
+
+  CARD_obj <- CARD::createCARDObject(
+	  sc_count = sc_count,
+	  sc_meta = sc_meta,
+	  spatial_count = spatial_count,
+	  spatial_location = spatial_location,
+	  ct.varname = "cellType",
+	  ct.select = unique(sc_meta$cellType),
+	  sample.varname = "sampleInfo",
+	  minCountGene = 100,
+	  minCountSpot = 5) 
+
+  CARD_obj <- CARD::CARD_deconvolution(CARD_object = CARD_obj)
+
+  metadata(sp_obj)$celltype_prop <- CARD_obj@Proportion_CARD
+
+  diff_list <- setdiff(colnames(counts(sp_obj)), rownames(sp_obj@metadata$celltype_prop))
+  current_colnames <- colnames(sp_obj)
+  columns_to_keep <- !current_colnames %in% diff_list
+  sp_obj <- sp_obj[, columns_to_keep]
+
+  return(sp_obj)
+}
+# spatial clustering