Fix GH token

.github/workflows/rworkflows.yml

@@ -42,10 +42,7 @@ jobs:
         run_pkgdown: ${{ true }}
         has_runit: ${{ false }}
         has_latex: ${{ false }}
-        GITHUB_TOKEN: ${{ secrets.PAT_GITHUB }}
+        GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
         run_docker: ${{ true }}
-        docker_user: bschilder
-        docker_org: neurogenomicslab
-        DOCKER_TOKEN: ${{ secrets.DOCKER_TOKEN }}
         runner_os: ${{ runner.os }}
         cache_version: cache-v1

DESCRIPTION

@@ -65,5 +65,5 @@ Remotes:
   github::aertslab/SCopeLoomR,
   github::scverse/anndataR
 VignetteBuilder: knitr
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.2
 Config/testthat/edition: 3

NEWS.md

@@ -27,7 +27,7 @@ and avoid conflicts with piggyback-oriented functions.
 - `is_class`
   - Add new classes: "matrix_strict", "matrix_sparse", "delayed_array"
 * `get_x`
-    - Add new args `slot` and `assay`
+    - Add new args `layer` and `assay`
 * New funcs: 
   - `get_obs_names`
   - `get_var_names`

R/calc_cor.R

@@ -13,7 +13,7 @@ calc_cor <- function(obj,
                      keys = NULL,
                      graph_key = NULL,
                      assay = NULL,
-                     slot = NULL,
+                     layer = NULL,
                      transpose = FALSE,
                      method = "pearson",
                      fill_na = NULL,
@@ -35,7 +35,7 @@ calc_cor <- function(obj,
       X <- get_x(
           obj = obj,
           assay = assay,
-          slot = slot,
+          layer = layer,
           transpose = transpose,
           n = 1,
           verbose = verbose)

R/get_cor.R

@@ -24,7 +24,7 @@
 get_cor <- function(obj,
                     keys = NULL,
                     assay = NULL,
-                    slot = NULL,
+                    layer = NULL,
                     graph_key = NULL,
                     method = "pearson",
                     return_obj = FALSE,
@@ -53,7 +53,7 @@ get_cor <- function(obj,
   if(is.null(Xcor)){
     Xcor <- calc_cor(obj = obj,
                      assay = assay,
-                     slot = slot,
+                     layer = layer,
                      keys = keys,
                      method = method)
   }

R/get_obsm.R

@@ -44,7 +44,7 @@ get_obsm <- function(obj,
   } else if (is_class(obj,"seurat")) {
     ## Seurat V1
     if(methods::is(obj,"seurat")){
-      ### Need a way to figure which slot names are availabe a priori ####
+      ### Need a way to figure which layer names are availabe a priori ####
       # messager("Extracting obsm from Seurat (V1).",v = verbose)
       # obsm <- list(PCA=list(embeddings=as.matrix([email protected]),
       #                             loadings=as.matrix([email protected])))
@@ -95,10 +95,10 @@ get_obsm <- function(obj,
     #   loadings="reducedDimA")
     obsm <- if(methods::.hasSlot(obj,"reducedDimS") &&
                ncol(obj@reducedDimS)==ncol(obj) ){
-      list(reducedDimS=t(methods::slot(obj, "reducedDimS")))
+      list(reducedDimS=t(methods::layer(obj, "reducedDimS")))
     } else if (methods::.hasSlot(obj,"reducedDimA") &&
                ncol(obj@reducedDimA)==ncol(obj) ) {
-      list(reducedDimA=t(methods::slot(obj, "reducedDimA")))
+      list(reducedDimA=t(methods::layer(obj, "reducedDimA")))
     } else {
       NULL
     }

R/get_uns.R

@@ -42,7 +42,7 @@ get_uns <- function(obj,
     uns <- lapply(stats::setNames(methods::slotNames(obj@experimentData),
                                   methods::slotNames(obj@experimentData)),
                   function(x){
-                    methods::slot(obj@experimentData,x)
+                    methods::layer(obj@experimentData,x)
                   })
     #### list ####
   } else if(is_class(obj,"list")){

R/get_variable_features.R

@@ -25,7 +25,7 @@ get_variable_features <- function(obj,
   }
   #### Check if empty ####
   if(length(Reduce(union,feat))==0){
-    messager("Warning:","Variable features slot was empty. Returning NULL.")
+    messager("Warning:","Variable features layer was empty. Returning NULL.")
     return(NULL)
   }
   #### Reduce list ####

R/get_varm.R

@@ -42,7 +42,7 @@ get_varm <- function(obj,
   } else if (is_class(obj,"seurat")) {
     ## Seurat V1
     if(methods::is(obj,"seurat")){
-      ### Need a way to figure which slot names are available a priori ####
+      ### Need a way to figure which layer names are available a priori ####
       # messager("Extracting varm from Seurat (V1).",v = verbose)
       # varm <- list(PCA=list(embeddings=as.matrix([email protected]),
       #                             loadings=as.matrix([email protected])))
@@ -105,7 +105,7 @@ get_varm <- function(obj,
     #   loadings="reducedDimA")
     varm <- if (methods::.hasSlot(obj,"reducedDimA") &&
                ncol(obj@reducedDimA)==nrow(obj) ) {
-      list(reducedDimA=t(methods::slot(obj, "reducedDimA")))
+      list(reducedDimA=t(methods::layer(obj, "reducedDimA")))
     } else {
       return(NULL)
     }

R/get_x.R

@@ -18,7 +18,7 @@ get_x <- function(obj,
                   n=NULL,
                   simplify=TRUE,
                   assay=NULL,
-                  slot=NULL,
+                  layer=NULL,
                   as_sparse=FALSE,
                   verbose=TRUE){
   # devoptera::args2vars(get_x)
@@ -55,16 +55,27 @@ get_x <- function(obj,
       data <- list(RNA.counts=obj@raw.data,
                    RNA.data=obj@data,
                    RNA.scale.data=obj@scale.data)
-    ## Seurat V2+
-    } else {
+    ## Seurat V2-5
+    } else if(packageVersion("Seurat")<"5") {
       assays <- obj@assays
       if(!is.null(assay)) assays[assays %in% assay]
       data <- lapply(assays,function(a){
         slots <- c("counts","data","scale.data")
         slots <- slots[sapply(slots,function(s){methods::.hasSlot(a,s)})]
-        if(!is.null(slot)) slots <- slots[slots %in% slot]
+        if(!is.null(layer)) slots <- slots[slots %in% layer]
         lapply(stats::setNames(slots,slots), function(s){
-          methods::slot(a,s)
+          methods::layer(a,s)
+        })
+      }) |> unlist(recursive = FALSE)
+    ## Seurat V5+
+    } else{
+      assays <- obj@assays
+      if(!is.null(assay)) assays <- assays[names(assays) %in% assay]
+      data <- lapply(assays,function(a){
+        layers <- SeuratObject::Layers(obj)
+        if(!is.null(layer)) layers <- intersect(layers,layer)
+        lapply(stats::setNames(layers,layers), function(s){
+          SeuratObject::LayerData(a,s)
         })
       }) |> unlist(recursive = FALSE)
     }

R/map_data_anndata.R

@@ -78,7 +78,7 @@ map_data_anndata <- function(obj,
     genes = rownames(assays[[1]]),
     original_rowdata = obj$var)
   #### Construct new SummarizedExperiment ####
-  ## Remove PC slot to avoid error:
+  ## Remove PC layer to avoid error:
   ## Error: ValueError: Value passed for key 'PCs' is of incorrect shape.
   obj$obsm$X_pca <- NULL
   obj$varm$PCs <- NULL

R/matrices_to_assayobjects.R

@@ -3,11 +3,11 @@
 #' Convert a named list of X_list to a named list of \pkg{Seurat}
 #' assay objects (see \link[SeuratObject]{CreateAssayObject}).
 #' @param X_list A named list of matrices (one per unique assay in
-#' \code{X_list}) to be put in the \code{counts} slot of each
+#' \code{X_list}) to be put in the \code{counts} layer of each
 #' \code{AssayObject}.
 #' @param var_features (Optional) A named list of feature metadata data.frames
 #'  (one per unique assay in \code{X_list}) to be put in the
-#'   \code{meta.features} slot of each \code{AssayObject}.
+#'   \code{meta.features} layer of each \code{AssayObject}.
 #' @inheritParams converters
 #' @returns A named list of \pkg{Seurat} assay objects.
 #'

R/set_obs.R

@@ -1,6 +1,6 @@
 #' Set unstructured data
 #'
-#' Set the sample observations slot (i.e. cell metadata)
+#' Set the sample observations layer (i.e. cell metadata)
 #'  in any single-cell object that has one.
 #' @param obs Observation metadata
 #' as a \link[base]{data.frame} with samples as row names.

R/set_uns.R

@@ -1,6 +1,6 @@
 #' Set unstructured data
 #'
-#' Set the unstructured data slot in any single-cell object that has one.
+#' Set the unstructured data layer in any single-cell object that has one.
 #' @param uns Unstructured data to be stored in object.
 #' @param key Name of the list element to store \code{uns} in.
 #' @inheritParams converters

R/set_var.R

@@ -1,6 +1,6 @@
 #' Set unstructured data
 #'
-#' Set the feature variable slot (i.e. gene metadata)
+#' Set the feature variable layer (i.e. gene metadata)
 #' in any single-cell object that has one.
 #' @param var Variable metadata
 #' as a \link[base]{data.frame} with features as row names.

R/seurat_to_anndata.R

@@ -7,17 +7,18 @@
 #' @export
 #' @examples
 #' obj <- example_obj("seurat")
-#' obj2 <- seurat_to_anndata(obj)
+#' obj2 <- seurat_to_anndata(obj, method="seuratdisk")
 seurat_to_anndata <- function(obj,
                               reimport = TRUE,
                               save_path = tempfile(fileext = ".h5ad"),
-                              method = c("sceasy","anndatar"),
+                              method = c("sceasy","anndatar","seuratdisk"),
                               verbose = TRUE,
                               ...){
 
   messager_to()
   method <- tolower(method)[1]
   #### Convert ####
+  if(!is.null(save_path)) save_path <- path.expand(save_path)
   # Method: anndatar
   if(method=="anndatar"){
     adat <- anndataR::from_Seurat(
@@ -29,7 +30,7 @@ seurat_to_anndata <- function(obj,
       },
       file = save_path
     )
-  } else {
+  } else if(method=="sceasy"){
     # Method: sceasy
     activate_conda(verbose=verbose)
     adat <- sceasy::convertFormat(obj = obj,
@@ -48,6 +49,12 @@ seurat_to_anndata <- function(obj,
                                save_path = save_path,
                                verbose = verbose)
     }
+  } else{
+    messager("Saving ==>",save_path)
+    h5Seurat_path <- gsub("\\.h5ad$",".h5Seurat",save_path)
+    SeuratDisk::SaveH5Seurat(obj, filename = h5Seurat_path)
+    SeuratDisk::Convert(h5Seurat_path, dest = "h5ad")
+    adat <- anndata::read_h5ad(save_path)
   }
   #### Return ###
   return(adat)