Seurat V5 compatability

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: clustifyr
 Title: Classifier for Single-cell RNA-seq Using Cell Clusters
-Version: 1.15.1
+Version: 1.15.2
 Description: Package designed to aid in classifying cells from single-cell RNA sequencing data
     using external reference data (e.g., bulk RNA-seq, scRNA-seq, microarray, gene lists). A 
     variety of correlation based methods and gene list enrichment methods are provided to assist cell
@@ -57,6 +57,7 @@ Imports:
     methods,
     SingleCellExperiment,
     SummarizedExperiment,
+    SeuratObject,
     matrixStats,
     S4Vectors,
     proxy,
@@ -73,7 +74,6 @@ Suggests:
     BiocManager,
     remotes,
     shiny,
-    SeuratObject,
     gprofiler2,
     purrr,
     data.table,
@@ -87,7 +87,7 @@ VignetteBuilder:
 ByteCompile: true
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 LazyData: true
 Config/Needs/website:
     pkgdown,

NAMESPACE

@@ -49,6 +49,7 @@ export(make_comb_ref)
 export(marker_select)
 export(matrixize_markers)
 export(object_data)
+export(object_loc_lookup)
 export(object_ref)
 export(overcluster)
 export(overcluster_test)
@@ -68,8 +69,10 @@ export(ref_marker_select)
 export(reverse_marker_matrix)
 export(run_clustifyr_app)
 export(run_gsea)
+export(sce_pbmc)
 export(seurat_meta)
 export(seurat_ref)
+export(so_pbmc)
 export(write_meta)
 import(Matrix)
 import(dplyr)
@@ -78,9 +81,16 @@ import(ggplot2)
 import(scales)
 import(tibble)
 importFrom(S4Vectors,DataFrame)
+importFrom(SeuratObject,"DefaultAssay<-")
+importFrom(SeuratObject,"Key<-")
+importFrom(SeuratObject,CreateDimReducObject)
+importFrom(SeuratObject,CreateSeuratObject)
+importFrom(SeuratObject,DefaultAssay)
+importFrom(SeuratObject,Key)
+importFrom(SeuratObject,VariableFeatures)
 importFrom(SingleCellExperiment,colData)
 importFrom(SingleCellExperiment,logcounts)
-importFrom(SummarizedExperiment,`colData<-`)
+importFrom(SummarizedExperiment,"colData<-")
 importFrom(cowplot,theme_cowplot)
 importFrom(fgsea,fgsea)
 importFrom(httr,build_url)
@@ -98,4 +108,5 @@ importFrom(stats,p.adjust)
 importFrom(stats,prcomp)
 importFrom(stats,quantile)
 importFrom(tidyr,gather)
+importFrom(utils,packageVersion)
 importFrom(utils,read.csv)

NEWS

@@ -52,4 +52,7 @@ Changes in version 1.7.3 (2022-03-09)
 + Maintainer change
 
 Changes in version 1.15.1 (2023-10-31)
-+ Replace `Seurat` dependency with `SeuratObject`
++ Replace `Seurat` dependency with `SeuratObject`
+
+Changes in version 1.15.2 (2024-04-03)
++ Add support for `Seurat` version 5 objects

R/clustifyR-package.R

@@ -17,5 +17,6 @@
 #' @importFrom cowplot theme_cowplot
 #' @importFrom fgsea fgsea
 #' @importFrom methods is
+#' @importFrom SeuratObject Key Key<- DefaultAssay DefaultAssay<-
 ## usethis namespace: end
 NULL

R/data.R

@@ -43,24 +43,6 @@
 #' @source `[pbmc_matrix]` processed by Seurat
 "pbmc_vargenes"
 
-#' Small clustered Seurat2 object
-#'
-#' @family data
-#' @source  `[pbmc_small]` processed by seurat
-"s_small"
-
-#' Small clustered Seurat3 object
-#'
-#' @family data
-#' @source  `[pbmc_small]` processed by Seurat
-"s_small3"
-
-#' Small SingleCellExperiment object
-#'
-#' @family data
-#' @source \url{https://github.com/hemberg-lab/scRNA.seq.datasets/blob/master/R/segerstolpe.R}
-"sce_small"
-
 #' reference matrix from seurat citeseq CBMC tutorial
 #'
 #' @family data
@@ -73,12 +55,6 @@
 #' @source \url{https://satijalab.org/seurat/v3.0/multimodal_vignette.html#identify-differentially-expressed-proteins-between-clusters}
 "cbmc_m"
 
-#' lookup table for single cell object structures
-#'
-#' @family data
-#' @source  various packages
-"object_loc_lookup"
-
 #' table of references stored in clustifyrdata
 #'
 #' @family data

R/main.R

@@ -59,7 +59,7 @@ clustify <- function(input, ...) {
 #'     metadata = pbmc_meta,
 #'     ref_mat = cbmc_ref,
 #'     query_genes = pbmc_vargenes,
-#'     cluster_col = "classified",
+#'     cluster_col = "RNA_snn_res.0.5",
 #'     verbose = TRUE
 #' )
 #'
@@ -69,28 +69,40 @@ clustify <- function(input, ...) {
 #'     metadata = pbmc_meta,
 #'     ref_mat = cbmc_ref,
 #'     query_genes = pbmc_vargenes,
-#'     cluster_col = "classified",
+#'     cluster_col = "RNA_snn_res.0.5",
 #'     compute_method = "cosine"
 #' )
-#'
+#' 
+#' # Annotate a SingleCellExperiment object
+#' sce <- sce_pbmc()
+#' clustify(
+#'     sce,
+#'     cbmc_ref,
+#'     cluster_col = "clusters",
+#'     obj_out = TRUE,
+#'     per_cell = FALSE,
+#'     dr = "umap"
+#' )
+#' 
 #' # Annotate a Seurat object
+#' so <- so_pbmc()
 #' clustify(
-#'     s_small3,
+#'     so,
 #'     cbmc_ref,
-#'     cluster_col = "RNA_snn_res.1",
+#'     cluster_col = "seurat_clusters",
 #'     obj_out = TRUE,
 #'     per_cell = FALSE,
-#'     dr = "tsne"
+#'     dr = "umap"
 #' )
 #'
 #' # Annotate (and return) a Seurat object per-cell
 #' clustify(
-#'     input = s_small3,
+#'     input = so,
 #'     ref_mat = cbmc_ref,
-#'     cluster_col = "RNA_snn_res.1",
+#'     cluster_col = "seurat_clusters",
 #'     obj_out = TRUE,
 #'     per_cell = TRUE,
-#'     dr = "tsne"
+#'     dr = "umap"
 #' )
 #' @export
 clustify.default <- function(input,
@@ -107,7 +119,7 @@ clustify.default <- function(input,
     lookuptable = NULL,
     rm0 = FALSE,
     obj_out = TRUE,
-    seurat_out = TRUE,
+    seurat_out = obj_out,
     vec_out = FALSE,
     rename_prefix = NULL,
     threshold = "auto",
@@ -161,8 +173,9 @@ clustify.default <- function(input,
         stop("given `cluster_col` is not a column in `metadata`", call. = FALSE)
     }
 
-    if (length(query_genes) == 0) {
-        message("var.features not found, using all genes instead")
+    if (is.null(query_genes) || length(query_genes) == 0) {
+        message("Variable features not available, using all genes instead\n",
+                "consider supplying variable features to `query_genes` argument.")
         query_genes <- NULL
     }
 
@@ -248,8 +261,8 @@ clustify.default <- function(input,
         message("similarity computation completed, matrix of ", dim(res)[1], " x ", dim(res)[2], ", preparing output")
     }
 
-    if ((obj_out &&
-        seurat_out) &&
+    obj_out <- seurat_out
+    if (obj_out &&
         !inherits(input_original, c(
             "matrix",
             "Matrix",
@@ -324,8 +337,8 @@ clustify.Seurat <- function(input,
     pseudobulk_method = "mean",
     use_var_genes = TRUE,
     dr = "umap",
-    seurat_out = TRUE,
     obj_out = TRUE,
+    seurat_out = obj_out,
     vec_out = FALSE,
     threshold = "auto",
     verbose = TRUE,
@@ -380,8 +393,8 @@ clustify.Seurat <- function(input,
     if (n_perm != 0) {
         res <- -log(res$p_val + .01, 10)
     }
-
-    if (!(seurat_out && obj_out) && !vec_out || vec) {
+    obj_out <- seurat_out
+    if (!obj_out && !vec_out || vec) {
         res
     } else {
         df_temp <- cor_to_call(
@@ -449,8 +462,8 @@ clustify.SingleCellExperiment <- function(input,
     pseudobulk_method = "mean",
     use_var_genes = TRUE,
     dr = "umap",
-    seurat_out = TRUE,
     obj_out = TRUE,
+    seurat_out = obj_out,
     vec_out = FALSE,
     threshold = "auto",
     verbose = TRUE,
@@ -501,8 +514,8 @@ clustify.SingleCellExperiment <- function(input,
     if (n_perm != 0) {
         res <- -log(res$p_val + .01, 10)
     }
-
-    if (!(seurat_out && obj_out) && !vec_out) {
+    obj_out <- seurat_out
+    if (!obj_out && !vec_out) {
         res
     } else {
         df_temp <- cor_to_call(
@@ -588,7 +601,7 @@ clustify_lists <- function(input, ...) {
 }
 
 #' @rdname clustify_lists
-#' @param input single-cell expression matrix or Seurat object
+#' @param input single-cell expression matrix, Seurat object, or SingleCellExperiment
 #' @param marker matrix or dataframe of candidate genes for each cluster
 #' @param marker_inmatrix whether markers genes are already in preprocessed
 #'   matrix form
@@ -658,7 +671,7 @@ clustify_lists.default <- function(input,
     output_high = TRUE,
     lookuptable = NULL,
     obj_out = TRUE,
-    seurat_out = TRUE,
+    seurat_out = obj_out,
     vec_out = FALSE,
     rename_prefix = NULL,
     threshold = 0,
@@ -778,10 +791,9 @@ clustify_lists.default <- function(input,
     if (verbose) {
         message("similarity computation completed, matrix of ", dim(res)[1], " x ", dim(res)[2], ", preparing output")
     }
-
+    obj_out <- seurat_out
     if ((!inherits(input_original, c("matrix", "Matrix", "data.frame")) &&
-        obj_out &&
-        seurat_out) || (vec_out &&
+        obj_out ) || (vec_out &&
                         inherits(input_original, c(
                             "matrix",
                             "Matrix",
@@ -840,8 +852,8 @@ clustify_lists.Seurat <- function(input,
     metric = "hyper",
     output_high = TRUE,
     dr = "umap",
-    seurat_out = TRUE,
     obj_out = TRUE,
+    seurat_out = obj_out,
     vec_out = FALSE,
     threshold = 0,
     rename_prefix = NULL,
@@ -885,8 +897,8 @@ clustify_lists.Seurat <- function(input,
         details_out = details_out,
         ...
     )
-
-    if (!(seurat_out && obj_out) && !vec_out || vec) {
+    obj_out <- seurat_out
+    if (!obj_out && !vec_out || vec) {
         res
     } else {
         if (metric != "consensus") {
@@ -943,8 +955,8 @@ clustify_lists.SingleCellExperiment <- function(input,
     metric = "hyper",
     output_high = TRUE,
     dr = "umap",
-    seurat_out = TRUE,
     obj_out = TRUE,
+    seurat_out = obj_out,
     vec_out = FALSE,
     threshold = 0,
     rename_prefix = NULL,
@@ -986,7 +998,7 @@ clustify_lists.SingleCellExperiment <- function(input,
         ...
     )
 
-    if (!(seurat_out && obj_out) && !vec_out || vec) {
+    if (!obj_out && !vec_out || vec) {
         res
     } else {
         df_temp <- cor_to_call(