Use Pizzarr for Zarr; More usage of Bioconductor classes

DESCRIPTION

@@ -24,7 +24,7 @@ LazyData: false
 Language: en-US
 StagedInstall: no
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 VignetteBuilder: knitr
 Imports:
     Matrix,

NAMESPACE

@@ -3,13 +3,17 @@
 export(get_giotto_obj)
 export(get_sce_obj)
 export(get_seurat_obj)
+export(get_seurat_v5_obj)
 export(get_spe_obj)
-export(giotto_to_anndata_zarr)
+export(giotto_to_spe)
 export(obj_list)
 export(sce_to_anndata_zarr)
-export(seurat_to_anndata_zarr)
+export(seurat_to_sce)
+export(seurat_to_spe)
 export(spe_to_anndata_zarr)
 export(spe_to_ome_zarr)
+import(Seurat)
+import(SeuratObject)
 importFrom(SingleCellExperiment,"reducedDims<-")
 importFrom(SingleCellExperiment,int_colData)
 importFrom(SingleCellExperiment,reducedDims)
@@ -19,7 +23,6 @@ importFrom(SummarizedExperiment,colData)
 importFrom(grDevices,as.raster)
 importFrom(grDevices,col2rgb)
 importFrom(methods,new)
-importFrom(methods,slot)
 importFrom(stats,rnorm)
 importFrom(stats,rpois)
 importFrom(stats,runif)

R/bioc_to_zarr.R

@@ -0,0 +1,127 @@
+#' Save a SingleCellExperiment to an AnnData-Zarr store.
+#'
+#' @param sce_obj The object to save.
+#' @param out_path A path to the output Zarr store.
+#' @return TRUE if the conversion succeeds.
+#'
+#' @export
+#' @examples
+#' obj <- get_sce_obj()
+#' sce_to_anndata_zarr(obj, out_path = "data/sce.zarr")
+#' @importFrom SingleCellExperiment reducedDims reducedDims<-
+sce_to_anndata_zarr <- function(sce_obj, out_path, to_dense = TRUE) {
+  obsm_keys <- names(as.list(reducedDims(sce_obj)))
+  for(obsm_key in obsm_keys) {
+    # If there are column names, then the obsm element will be stored as a data.frame,
+    # but Vitessce can only handle array obsm, so we need to remove any column names.
+    # Reference: https://github.com/theislab/zellkonverter/blob/e1e95b1/R/SCE2AnnData.R#L159
+    colnames(reducedDims(sce_obj)[[obsm_key]]) <- NULL
+  }
+
+  store <- pizzarr::DirectoryStore$new(out_path)
+  anndataR::from_SingleCellExperiment(sce_obj, "ZarrAnnData", store = store, to_dense = to_dense)
+  return(TRUE)
+}
+
+#' Save a SpatialExperiment to an AnnData-Zarr store.
+#'
+#' @param spe_obj The object to save.
+#' @param out_path A path to the output Zarr store.
+#' @return TRUE if the conversion succeeds.
+#'
+#' @export
+#' @importFrom SummarizedExperiment colData
+#' @importFrom SingleCellExperiment int_colData
+#' @importFrom SpatialExperiment colData<-
+spe_to_anndata_zarr <- function(spe_obj, out_path) {
+  internal_col_data <- int_colData(spe_obj)
+
+  colData(spe_obj) <- cbind(
+    colData(spe_obj),
+    internal_col_data$spatialCoords,
+    # spatialData deprecated in 1.5.2
+    # internal_col_data$spatialData,
+    internal_col_data$reducedDims
+  )
+
+  success <- sce_to_anndata_zarr(spe_obj, out_path)
+  return(success)
+}
+
+#' Save an image in a SpatialExperiment to an OME-Zarr store
+#'
+#' @param spe_obj The object containing the image.
+#' @param sample_id The sample_id in the imgData data frame.
+#' @param image_id The image_id in the imgData data frame.
+#' @param out_path A path to the output Zarr store.
+#' @return TRUE if the conversion succeeds.
+#'
+#' @export
+#' @examples
+#' obj <- get_spe_obj()
+#' spe_to_ome_zarr(obj, "sample1", "image1", "data/spe_image.zarr")
+#' @importFrom SpatialExperiment getImg
+#' @importFrom grDevices as.raster col2rgb
+spe_to_ome_zarr <- function(spe_obj, sample_id, image_id, out_path) {
+  img_arr <- apply(as.matrix(as.raster(getImg(spe_obj, image_id = image_id, sample_id = sample_id))), c(1, 2), col2rgb)
+
+  # Use basilisk
+  proc <- basilisk::basiliskStart(py_env)
+  on.exit(basilisk::basiliskStop(proc))
+
+  success <- basilisk::basiliskRun(proc, function(img_arr, sample_id, image_id, out_path) {
+    zarr <- reticulate::import("zarr")
+    ome_zarr <- reticulate::import("ome_zarr")
+
+    z_root <- zarr$open_group(out_path, mode = "w")
+
+    # Need to copy this here since can't refer to functions in the outside environment.
+    obj_list <- function(...) {
+      retval <- stats::setNames(list(), character(0))
+      param_list <- list(...)
+      for(key in names(param_list)) {
+        retval[[key]] = param_list[[key]]
+      }
+      retval
+    }
+
+    default_window <- obj_list(
+      start = 0,
+      min = 0,
+      max = 255,
+      end = 255
+    )
+
+    ome_zarr$writer$write_image(
+      image = img_arr,
+      group = z_root,
+      axes = "cyx",
+      omero = obj_list(
+        name = image_id,
+        version = "0.3",
+        rdefs = obj_list(
+
+        ),
+        channels = list(
+          obj_list(
+            label = "r",
+            color = "FF0000",
+            window = default_window
+          ),
+          obj_list(
+            label = "g",
+            color = "00FF00",
+            window = default_window
+          ),
+          obj_list(
+            label = "b",
+            color = "0000FF",
+            window = default_window
+          )
+        )
+      )
+    )
+    return(TRUE)
+  }, img_arr = img_arr, sample_id = sample_id, image_id = image_id, out_path = out_path)
+  return(success)
+}