Fix alive module

.github/workflows/rworkflows.yml

@@ -40,6 +40,12 @@ jobs:
           cont: ~
           rspm: ~
     steps:
+    - name: Prefer source installs on macOS as fallback (Bioc 3.23 mac binary gap)
+      if: runner.os == 'macOS'
+      run: |
+        mkdir -p ~/.R
+        echo 'options(install.packages.check.source = "no", pkgType = "source")' >> ~/.Rprofile
+      shell: bash
     - uses: neurogenomics/rworkflows@master
       with:
         run_bioccheck: ${{ false }}
@@ -56,4 +62,4 @@ jobs:
         DOCKER_TOKEN: ${{ secrets.DOCKER_TOKEN }}
         runner_os: ${{ runner.os }}
         cache_version: cache-v1
-        docker_registry: ghcr.io
+        docker_registry: ghcr.io

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: HPCell
 Title: Massively-Parallel R Native Pipeline for Single-Cell Analysis
-Version: 0.5.0
+Version: 0.5.1
 Authors@R: c(person("Stefano", "Mangiola", email = "mangiolastefano@gmail.com",
                   role = c("aut", "cre")),
                   person("Jiayi", "Si", email = "si.j@wehi.edu.au",
@@ -40,7 +40,6 @@ Imports:
   EnsDb.Hsapiens.v86,
   scater,
   SingleR,
-  celldex,
   scuttle,
   scDblFinder,
   magrittr,
@@ -74,6 +73,7 @@ Imports:
   rhdf5
 Suggests: 
     testthat (>= 3.0.0),
+    celldex,
     qs,
     Azimuth,
     CellChat,

NAMESPACE

@@ -156,8 +156,6 @@ importFrom(SummarizedExperiment,rowData)
 importFrom(biomaRt,getBM)
 importFrom(biomaRt,useMart)
 importFrom(callr,r)
-importFrom(celldex,BlueprintEncodeData)
-importFrom(celldex,MonacoImmuneData)
 importFrom(crew,crew_controller_local)
 importFrom(data.table,":=")
 importFrom(digest,digest)

R/functions.R

@@ -48,7 +48,7 @@ empty_droplet_id <- function(input_read_RNA_assay,
 
   # Get counts
   if (inherits(input_read_RNA_assay, "Seurat")) {
-    counts <- GetAssayData(input_read_RNA_assay, assay, slot = "counts")
+    counts <- GetAssayData(input_read_RNA_assay, assay, layer = "counts")
   } else if (inherits(input_read_RNA_assay, "SingleCellExperiment")) {
     counts <- assay(input_read_RNA_assay, assay)
   }
@@ -269,7 +269,7 @@ empty_droplet_threshold<- function(input_read_RNA_assay,
 
   # Get counts
   if (inherits(input_read_RNA_assay, "Seurat")) {
-    counts <- GetAssayData(input_read_RNA_assay, assay, slot = "counts")
+    counts <- GetAssayData(input_read_RNA_assay, assay, layer = "counts")
   } else if (inherits(input_read_RNA_assay, "SingleCellExperiment")) {
     counts <- assay(input_read_RNA_assay, assay)
   }
@@ -312,8 +312,6 @@ empty_droplet_threshold<- function(input_read_RNA_assay,
 #'
 #' @return A tibble with cell-type annotation data.
 #'
-#' @importFrom celldex BlueprintEncodeData
-#' @importFrom celldex MonacoImmuneData
 #' 
 #' @importFrom Seurat CreateAssayObject
 #' @importFrom Seurat SCTransform
@@ -390,6 +388,12 @@ annotation_label_transfer <- function(input_read_RNA_assay,
     colnames(input_read_RNA_assay)[2]= "dummy___"
   }
 
+  if (!requireNamespace("celldex", quietly = TRUE))
+    stop(
+      "Package 'celldex' is required for SingleR-based cell-type annotation. ",
+      "Install it with: BiocManager::install('celldex')"
+    )
+
   #snapshotDate(): 2025-10-29
   blueprint <- celldex::BlueprintEncodeData(
     ensembl = feature_nomenclature == "ensembl"
@@ -634,7 +638,7 @@ alive_identification <- function(input_read_RNA_assay,
 
 
   if (inherits(input_read_RNA_assay, "Seurat")) {
-    counts <- GetAssayData(input_read_RNA_assay, assay = assay, slot = "counts")
+    counts <- GetAssayData(input_read_RNA_assay, assay = assay, layer = "counts")
     if (!any(str_which(colnames(input_read_RNA_assay[[]]), nFeature_name)) ||
         !any(str_which(colnames(input_read_RNA_assay[[]]), nCount_name))) {
       input_read_RNA_assay[[nFeature_name]] <-
@@ -661,21 +665,19 @@ alive_identification <- function(input_read_RNA_assay,
 
   # Returns a named vector of IDs
   # Matches the gene id's row by row and inserts NA when it can't find gene names
-  if (feature_nomenclature == "symbol") {
-    location <- mapIds(
+  location <- mapIds(
       EnsDb.Hsapiens.v86,
-      keys=rownames(input_read_RNA_assay),
-      column="SEQNAME",
-      keytype="SYMBOL"
+      keys = rownames(input_read_RNA_assay),
+      column = "SEQNAME",
+      keytype = if (feature_nomenclature == "symbol") "SYMBOL" else "GENEID"
     )
-  }
 
 
-  which_mito = rownames(input_read_RNA_assay) |> str_which("^MT")
+  which_mito = which(location == "MT")
 
   # mitochondrion =
   #   input_read_RNA_assay |>
-  #   GetAssayData( slot = "counts", assay=assay) |>
+  #   GetAssayData( layer = "counts", assay=assay) |>
   # 
   #   # Join mitochondrion statistics
   #   # Compute per-cell quality control metrics for a count matrix or a SingleCellExperiment