Merge pull request #30 from msraredon/dev_master

Updated NICHES to be compatible with Seurat V5
msraredon · Mar 3, 2024 · 4650e48 · 4650e48
2 parents 96ad10f + 858c90d
commit 4650e48
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -7,7 +7,7 @@ Description: Cell-cell Interactions at Single-Cell Resolution
 License: GPL-3
 Encoding: UTF-8
 LazyData: yes
-RoxygenNote: 7.1.2
+RoxygenNote: 7.2.3
 VignetteBuilder: knitr
 Depends:
     R (>= 4.0)

diff --git a/R/RunCellToCell.R b/R/RunCellToCell.R
@@ -38,7 +38,7 @@ RunCellToCell <- function(sys.small,
       colnames(subunit.list[[s]]) <- colnames(temp)
       rownames(subunit.list[[s]]) <- rownames(ground.truth$source.subunits)
       non.na.indices <- !is.na(ground.truth$source.subunits[,s]) #Identify rows in the s-th column of the ground truth which are not NA
-      subunit.list[[s]][non.na.indices,] <- as.matrix(temp@assays[[assay]]@data[ground.truth$source.subunits[non.na.indices,s],])   #For every row in the initialized matrix corresponding to the indices of the ground.truth which are not NA, replace with the rows from the Seurat object corresponding to the genes in the ground.truth at those indices
+      subunit.list[[s]][non.na.indices,] <- as.matrix(getSeuratAssay(temp,assay,"data")[ground.truth$source.subunits[non.na.indices,s],])   #For every row in the initialized matrix corresponding to the indices of the ground.truth which are not NA, replace with the rows from the Seurat object corresponding to the genes in the ground.truth at those indices
     }
     lig.list[[i]] <- Reduce('*',subunit.list)
     rm(subunit.list)
@@ -54,7 +54,7 @@ RunCellToCell <- function(sys.small,
       colnames(subunit.list[[t]]) <- colnames(temp)
       rownames(subunit.list[[t]]) <- rownames(ground.truth$target.subunits)
       non.na.indices <- !is.na(ground.truth$target.subunits[,t]) #Identify rows in the t-th column of the ground truth which are not NA
-      subunit.list[[t]][non.na.indices,] <- as.matrix(temp@assays[[assay]]@data[ground.truth$target.subunits[non.na.indices,t],])   #For every row in the initialized matrix corresponding to the indices of the ground.truth which are not NA, replace with the rows from the Seurat object corresponding to the genes in the ground.truth at those indices
+      subunit.list[[t]][non.na.indices,] <- as.matrix(getSeuratAssay(temp,assay,"data")[ground.truth$target.subunits[non.na.indices,t],])   #For every row in the initialized matrix corresponding to the indices of the ground.truth which are not NA, replace with the rows from the Seurat object corresponding to the genes in the ground.truth at those indices
     }
     rec.list[[i]] <- Reduce('*',subunit.list)
     rm(subunit.list)
@@ -108,6 +108,13 @@ RunCellToCell <- function(sys.small,
 
   #Use this matrix to create a Seurat object:
   demo <- Seurat::CreateSeuratObject(counts = as.matrix(scc),assay = 'CellToCell')
+  # JC: Seurat V5 will not create data slot automatically, the following step is to manually add this slot
+  if(SeuratObject::Version(demo) >= 5){
+    demo <- NormalizeData(demo,assay = "CellToCell")  # Seura Object need to be >= 5.0.1
+    demo@assays$CellToCell@layers$data <- demo@assays$CellToCell@layers$counts # Seura Object need to be>= 5.0.1
+
+  }
+
 
   # Gather and assemble metadata based on "ident" slot
   sending.cell.idents.2 <- do.call(c,sending.cell.idents)
@@ -139,7 +146,8 @@ RunCellToCell <- function(sys.small,
   # Compile
   meta.data.to.add.also <- cbind(sending.metadata,receiving.metadata,joint.metadata)
   rownames(meta.data.to.add.also) <- paste(sending.barcodes,receiving.barcodes,sep='—')
-  # Add additional metadata
+  # Add additional metadata 
+  ### COMMENT 2024-02-03 MSBR: Is this compatible with Seurat v5?###
   demo <- Seurat::AddMetaData(demo,metadata = as.data.frame(meta.data.to.add.also))
   }
   # Define initial identity
@@ -152,7 +160,7 @@ RunCellToCell <- function(sys.small,
   else{
     output_list <- vector(mode = "list",length=2)
     names(output_list) <- c("CellToCellMatrix","metadata")
-    output_list[["CellToCellMatrix"]] <- demo[["CellToCell"]]@counts
+    output_list[["CellToCellMatrix"]] <- getSeuratAssay(demo,"CellToCell","counts")
     output_list[["metadata"]] <- demo@meta.data
     return(output_list)
   }

diff --git a/R/RunCellToCellSpatial.R b/R/RunCellToCellSpatial.R
@@ -26,11 +26,11 @@ RunCellToCellSpatial <- function(sys.small,
 
     subunit.list <- list() # Builds sending (ligand) data for any number of ligand subunits
     for (s in 1:ncol(ground.truth$source.subunits)){ #For each subunit column...
-      subunit.list[[s]] <- matrix(data = 1,nrow = nrow(ground.truth$source.subunits),ncol = ncol(sys.small@assays[[assay]]@data[,edgelist$from])) #initialize a mechanism x barcode matrix of all NAs
-      colnames(subunit.list[[s]]) <- colnames(sys.small@assays[[assay]]@data[,edgelist$from])
+      subunit.list[[s]] <- matrix(data = 1,nrow = nrow(ground.truth$source.subunits),ncol = ncol(getSeuratAssay(sys.small,assay,"data")[,edgelist$from])) #initialize a mechanism x barcode matrix of all NAs
+      colnames(subunit.list[[s]]) <- colnames(getSeuratAssay(sys.small,assay,"data")[,edgelist$from])
       rownames(subunit.list[[s]]) <- rownames(ground.truth$source.subunits)
       non.na.indices <- !is.na(ground.truth$source.subunits[,s]) #Identify rows in the s-th column of the ground truth which are not NA
-      subunit.list[[s]][non.na.indices,] <- as.matrix(sys.small@assays[[assay]]@data[ground.truth$source.subunits[non.na.indices,s],edgelist$from])   #For every row in the initialized matrix corresponding to the indices of the ground.truth which are not NA, replace with the rows from the Seurat object corresponding to the genes in the ground.truth at those indices
+      subunit.list[[s]][non.na.indices,] <- as.matrix(getSeuratAssay(sys.small,assay,"data")[ground.truth$source.subunits[non.na.indices,s],edgelist$from])   #For every row in the initialized matrix corresponding to the indices of the ground.truth which are not NA, replace with the rows from the Seurat object corresponding to the genes in the ground.truth at those indices
     }
     lig.data <- Reduce('*',subunit.list)
     rm(subunit.list)
@@ -41,11 +41,11 @@ RunCellToCellSpatial <- function(sys.small,
 
     subunit.list <- list() # Builds receiving (receptor) data for any number of receptor subunits
     for (t in 1:ncol(ground.truth$target.subunits)){
-      subunit.list[[t]] <- matrix(data = 1,nrow = nrow(ground.truth$target.subunits),ncol = ncol(sys.small@assays[[assay]]@data[,edgelist$to])) #initialize a mechanism x barcode matrix of all NAs
-      colnames(subunit.list[[t]]) <- colnames(sys.small@assays[[assay]]@data[,edgelist$to])
+      subunit.list[[t]] <- matrix(data = 1,nrow = nrow(ground.truth$target.subunits),ncol = ncol(getSeuratAssay(sys.small,assay,"data")[,edgelist$to])) #initialize a mechanism x barcode matrix of all NAs
+      colnames(subunit.list[[t]]) <- colnames(getSeuratAssay(sys.small,assay,"data")[,edgelist$to])
       rownames(subunit.list[[t]]) <- rownames(ground.truth$target.subunits)
       non.na.indices <- !is.na(ground.truth$target.subunits[,t]) #Identify rows in the t-th column of the ground truth which are not NA
-      subunit.list[[t]][non.na.indices,] <- as.matrix(sys.small@assays[[assay]]@data[ground.truth$target.subunits[non.na.indices,t],edgelist$to])   #For every row in the initialized matrix corresponding to the indices of the ground.truth which are not NA, replace with the rows from the Seurat object corresponding to the genes in the ground.truth at those indices
+      subunit.list[[t]][non.na.indices,] <- as.matrix(getSeuratAssay(sys.small,assay,"data")[ground.truth$target.subunits[non.na.indices,t],edgelist$to])   #For every row in the initialized matrix corresponding to the indices of the ground.truth which are not NA, replace with the rows from the Seurat object corresponding to the genes in the ground.truth at those indices
     }
     rec.data <- Reduce('*',subunit.list)
     rm(subunit.list)
@@ -61,6 +61,13 @@ RunCellToCellSpatial <- function(sys.small,
   # Use this matrix to create a Seurat object:
   demo <- Seurat::CreateSeuratObject(counts = as.matrix(scc),assay = 'CellToCellSpatial')
 
+  # JC: Seurat V5 will not create data slot automatically, the following step is to manually add this slot
+  if(SeuratObject::Version(demo) >= 5){
+    demo <- NormalizeData(demo,assay = "CellToCellSpatial")  # Seura Object need to be >= 5.0.1
+    demo@assays$CellToCellSpatial@layers$data <- demo@assays$CellToCellSpatial@layers$counts # Seura Object need to be >= 5.0.1
+
+  }
+
   # Add key metadata
 
   meta.data.to.add <- data.frame(SendingType = sending.cell.idents,
@@ -73,7 +80,7 @@ RunCellToCellSpatial <- function(sys.small,
 
   #Add metadata to the Seurat object
   demo <- Seurat::AddMetaData(demo,metadata = meta.data.to.add)
-
+  
   # Gather and assemble additional metadata
   if (!is.null(meta.data.to.map)){
     # Identify sending and receiving barcodes
@@ -107,7 +114,7 @@ RunCellToCellSpatial <- function(sys.small,
   else{
     output_list <- vector(mode = "list",length=2)
     names(output_list) <- c("CellToCellSpatialMatrix","metadata")
-    output_list[["CellToCellSpatialMatrix"]] <- demo[["CellToCellSpatial"]]@counts
+    output_list[["CellToCellSpatialMatrix"]] <- getSeuratAssay(demo,"CellToCellSpatial","counts")
     output_list[["metadata"]] <- demo@meta.data
     return(output_list)
   }

diff --git a/R/RunCellToNeighborhood.R b/R/RunCellToNeighborhood.R
@@ -25,11 +25,11 @@ RunCellToNeighborhood <- function(sys.small,
 
   subunit.list <- list() # Builds sending (ligand) data for any number of ligand subunits
   for (s in 1:ncol(ground.truth$source.subunits)){ #For each subunit column...
-    subunit.list[[s]] <- matrix(data = 1,nrow = nrow(ground.truth$source.subunits),ncol = ncol(sys.small@assays[[assay]]@data[,edgelist$from])) #initialize a mechanism x barcode matrix of all NAs
-    colnames(subunit.list[[s]]) <- colnames(sys.small@assays[[assay]]@data[,edgelist$from])
+    subunit.list[[s]] <- matrix(data = 1,nrow = nrow(ground.truth$source.subunits),ncol = ncol(getSeuratAssay(sys.small,assay,"data")[,edgelist$from])) #initialize a mechanism x barcode matrix of all NAs
+    colnames(subunit.list[[s]]) <- colnames(getSeuratAssay(sys.small,assay,"data")[,edgelist$from])
     rownames(subunit.list[[s]]) <- rownames(ground.truth$source.subunits)
     non.na.indices <- !is.na(ground.truth$source.subunits[,s]) #Identify rows in the s-th column of the ground truth which are not NA
-    subunit.list[[s]][non.na.indices,] <- as.matrix(sys.small@assays[[assay]]@data[ground.truth$source.subunits[non.na.indices,s],edgelist$from])   #For every row in the initialized matrix corresponding to the indices of the ground.truth which are not NA, replace with the rows from the Seurat object corresponding to the genes in the ground.truth at those indices
+    subunit.list[[s]][non.na.indices,] <- as.matrix(getSeuratAssay(sys.small,assay,"data")[ground.truth$source.subunits[non.na.indices,s],edgelist$from])   #For every row in the initialized matrix corresponding to the indices of the ground.truth which are not NA, replace with the rows from the Seurat object corresponding to the genes in the ground.truth at those indices
   }
   lig.data <- Reduce('*',subunit.list)
   rm(subunit.list)
@@ -40,11 +40,11 @@ RunCellToNeighborhood <- function(sys.small,
 
   subunit.list <- list() # Builds receiving (receptor) data for any number of receptor subunits
   for (t in 1:ncol(ground.truth$target.subunits)){
-    subunit.list[[t]] <- matrix(data = 1,nrow = nrow(ground.truth$target.subunits),ncol = ncol(sys.small@assays[[assay]]@data[,edgelist$to])) #initialize a mechanism x barcode matrix of all NAs
-    colnames(subunit.list[[t]]) <- colnames(sys.small@assays[[assay]]@data[,edgelist$to])
+    subunit.list[[t]] <- matrix(data = 1,nrow = nrow(ground.truth$target.subunits),ncol = ncol(getSeuratAssay(sys.small,assay,"data")[,edgelist$to])) #initialize a mechanism x barcode matrix of all NAs
+    colnames(subunit.list[[t]]) <- colnames(getSeuratAssay(sys.small,assay,"data")[,edgelist$to])
     rownames(subunit.list[[t]]) <- rownames(ground.truth$target.subunits)
     non.na.indices <- !is.na(ground.truth$target.subunits[,t]) #Identify rows in the t-th column of the ground truth which are not NA
-    subunit.list[[t]][non.na.indices,] <- as.matrix(sys.small@assays[[assay]]@data[ground.truth$target.subunits[non.na.indices,t],edgelist$to])   #For every row in the initialized matrix corresponding to the indices of the ground.truth which are not NA, replace with the rows from the Seurat object corresponding to the genes in the ground.truth at those indices
+    subunit.list[[t]][non.na.indices,] <- as.matrix(getSeuratAssay(sys.small,assay,"data")[ground.truth$target.subunits[non.na.indices,t],edgelist$to])   #For every row in the initialized matrix corresponding to the indices of the ground.truth which are not NA, replace with the rows from the Seurat object corresponding to the genes in the ground.truth at those indices
   }
   rec.data <- Reduce('*',subunit.list)
   rm(subunit.list)
@@ -67,7 +67,13 @@ RunCellToNeighborhood <- function(sys.small,
 
   # Use this matrix to create a Seurat object:
   demo <- Seurat::CreateSeuratObject(counts = as.matrix(scc),assay = 'CellToNeighborhood')
-
+  # JC: Seurat V5 will not create data slot automatically, the following step is to manually add this slot
+  if(SeuratObject::Version(demo) >= 5){
+    demo <- NormalizeData(demo,assay = "CellToNeighborhood")  # Seura Object need to be >= 5.0.1
+    demo@assays$CellToNeighborhood@layers$data <- demo@assays$CellToNeighborhood@layers$counts # Seura Object need to be >= 5.0.1
+
+  }
+
   # Add metadata based on ident slot
   demo <- Seurat::AddMetaData(demo,metadata = barcodes,col.name = 'SendingCell')
   # bug fix: add the Neighborhood - prefix
@@ -107,7 +113,7 @@ RunCellToNeighborhood <- function(sys.small,
   else{
     output_list <- vector(mode = "list",length=2)
     names(output_list) <- c("CellToNeighborhoodMatrix","metadata")
-    output_list[["CellToNeighborhoodMatrix"]] <- demo[["CellToNeighborhood"]]@counts
+    output_list[["CellToNeighborhoodMatrix"]] <- getSeuratAssay(demo,"CellToNeighborhood","counts")
     output_list[["metadata"]] <- demo@meta.data
     return(output_list)
   }

diff --git a/R/RunCellToSystem.R b/R/RunCellToSystem.R
@@ -37,7 +37,7 @@ RunCellToSystem <- function(sys.small,
     colnames(subunit.list[[t]]) <- colnames(sys.small)
     rownames(subunit.list[[t]]) <- rownames(ground.truth$target.subunits)
     non.na.indices <- !is.na(ground.truth$target.subunits[,t]) #Identify rows in the s-th column of the ground truth which are not NA
-    subunit.list[[t]][non.na.indices,] <- as.matrix(sys.small@assays[[assay]]@data[ground.truth$target.subunits[non.na.indices,t],])   #For every row in the initialized matrix corresponding to the indices of the ground.truth which are not NA, replace with the rows from the Seurat object corresponding to the genes in the ground.truth at those indices
+    subunit.list[[t]][non.na.indices,] <- as.matrix(getSeuratAssay(sys.small,assay,"data")[ground.truth$target.subunits[non.na.indices,t],])   #For every row in the initialized matrix corresponding to the indices of the ground.truth which are not NA, replace with the rows from the Seurat object corresponding to the genes in the ground.truth at those indices
   }
   rec.map <- Reduce('*',subunit.list)
   rm(subunit.list)
@@ -65,7 +65,7 @@ RunCellToSystem <- function(sys.small,
     colnames(subunit.list[[s]]) <- colnames(sys.small)
     rownames(subunit.list[[s]]) <- rownames(ground.truth$source.subunits)
     non.na.indices <- !is.na(ground.truth$source.subunits[,s]) #Identify rows in the s-th column of the ground truth which are not NA
-    subunit.list[[s]][non.na.indices,] <- as.matrix(sys.small@assays[[assay]]@data[ground.truth$source.subunits[non.na.indices,s],])   #For every row in the initialized matrix corresponding to the indices of the ground.truth which are not NA, replace with the rows from the Seurat object corresponding to the genes in the ground.truth at those indices
+    subunit.list[[s]][non.na.indices,] <- as.matrix(getSeuratAssay(sys.small,assay,"data")[ground.truth$source.subunits[non.na.indices,s],])   #For every row in the initialized matrix corresponding to the indices of the ground.truth which are not NA, replace with the rows from the Seurat object corresponding to the genes in the ground.truth at those indices
   }
   lig.map <- Reduce('*',subunit.list)
   rm(subunit.list)
@@ -82,6 +82,12 @@ RunCellToSystem <- function(sys.small,
 
   # Use this matrix to create a Seurat object:
   demo <- Seurat::CreateSeuratObject(counts = as.matrix(sc.connectome),assay = 'CellToSystem')
+  # JC: Seurat V5 will not create data slot automatically, the following step is to manually add this slot
+  if(SeuratObject::Version(demo) >= 5){
+    demo <- NormalizeData(demo,assay = "CellToSystem")  # Seura Object need to be >= 5.0.1
+    demo@assays$CellToSystem@layers$data <- demo@assays$CellToSystem@layers$counts # Seura Object need to be >= 5.0.1
+
+  }
 
   # Add metadata to the Seurat object
   meta.data.to.add <- data.frame(as.character(colnames(lig.map)))
@@ -126,7 +132,7 @@ RunCellToSystem <- function(sys.small,
   else{
     output_list <- vector(mode = "list",length=2)
     names(output_list) <- c("CellToSystemMatrix","metadata")
-    output_list[["CellToSystemMatrix"]] <- demo[["CellToSystem"]]@counts
+    output_list[["CellToSystemMatrix"]] <- getSeuratAssay(demo,"CellToSystem","counts")
     output_list[["metadata"]] <- demo@meta.data
     return(output_list)
   }