Merge pull request #952 from drieslab/suite_dev

v4.0.6
drieslab · May 13, 2024 · 621cde5 · 621cde5
2 parents af27e62 + 14faf9c
commit 621cde5
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diff --git a/.github/workflows/main_check.yaml b/.github/workflows/main_check.yaml
@@ -9,10 +9,6 @@ on:
     branches:
       - 'suite'
       - 'suite_dev'
-  # pull_request:
-  #   branches:
-  #     - 'suite'
-  #     - 'suite_dev'
 
 permissions:
   contents: read

diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: Giotto
 Title: Spatial Single-Cell Transcriptomics Toolbox
-Version: 4.0.5
+Version: 4.0.6
 Authors@R: c(
 	person("Ruben", "Dries", email = "[email protected]",
 		 role = c("aut", "cre")),
@@ -32,7 +32,7 @@ Depends:
     utils (>= 3.5.0),
     R (>= 3.5.0),
     methods,
-    GiottoClass (>= 0.2.0)
+    GiottoClass (>= 0.3.0)
 Imports:
     BiocParallel,
     BiocSingular,
@@ -43,7 +43,7 @@ Imports:
     ggplot2 (>= 3.1.1),
     ggrepel,
     GiottoUtils (>= 0.1.6),
-    GiottoVisuals (>= 0.1.1),
+    GiottoVisuals (>= 0.2.0),
     igraph (>= 1.2.4.1),
     jsonlite,
     limma,
@@ -148,6 +148,7 @@ Collate:
     'suite_reexports.R'
     'image_registration.R'
     'interactivity.R'
+    'kriging.R'
     'package_imports.R'
     'poly_influence.R'
     'python_hmrf.R'

diff --git a/NAMESPACE b/NAMESPACE
@@ -156,6 +156,7 @@ export(detectSpatialPatterns)
 export(dimCellPlot)
 export(dimCellPlot2D)
 export(dimFeatPlot2D)
+export(dimFeatPlot3D)
 export(dimGenePlot3D)
 export(dimPlot)
 export(dimPlot2D)
@@ -429,12 +430,14 @@ export(spatDeconvPlot)
 export(spatDimCellPlot)
 export(spatDimCellPlot2D)
 export(spatDimFeatPlot2D)
+export(spatDimFeatPlot3D)
 export(spatDimGenePlot3D)
 export(spatDimPlot)
 export(spatDimPlot2D)
 export(spatDimPlot3D)
 export(spatFeatPlot2D)
 export(spatFeatPlot2D_single)
+export(spatFeatPlot3D)
 export(spatGenePlot3D)
 export(spatIDs)
 export(spatInSituPlotDensity)
@@ -484,12 +487,13 @@ export(violinPlot)
 export(wrap)
 export(writeGiottoLargeImage)
 export(writeHMRFresults)
+exportMethods(interpolateFeature)
 import(GiottoClass)
 import(GiottoUtils)
 import(GiottoVisuals)
 import(ggplot2)
 import(methods)
-import(stats)
+import(stats, except = density)
 import(utils)
 importClassesFrom(data.table,data.table)
 importFrom(GiottoClass,"activeFeatType<-")
@@ -716,6 +720,7 @@ importFrom(GiottoVisuals,addGiottoImageToSpatPlot)
 importFrom(GiottoVisuals,dimCellPlot)
 importFrom(GiottoVisuals,dimCellPlot2D)
 importFrom(GiottoVisuals,dimFeatPlot2D)
+importFrom(GiottoVisuals,dimFeatPlot3D)
 importFrom(GiottoVisuals,dimGenePlot3D)
 importFrom(GiottoVisuals,dimPlot)
 importFrom(GiottoVisuals,dimPlot2D)
@@ -750,12 +755,14 @@ importFrom(GiottoVisuals,spatDeconvPlot)
 importFrom(GiottoVisuals,spatDimCellPlot)
 importFrom(GiottoVisuals,spatDimCellPlot2D)
 importFrom(GiottoVisuals,spatDimFeatPlot2D)
+importFrom(GiottoVisuals,spatDimFeatPlot3D)
 importFrom(GiottoVisuals,spatDimGenePlot3D)
 importFrom(GiottoVisuals,spatDimPlot)
 importFrom(GiottoVisuals,spatDimPlot2D)
 importFrom(GiottoVisuals,spatDimPlot3D)
 importFrom(GiottoVisuals,spatFeatPlot2D)
 importFrom(GiottoVisuals,spatFeatPlot2D_single)
+importFrom(GiottoVisuals,spatFeatPlot3D)
 importFrom(GiottoVisuals,spatGenePlot3D)
 importFrom(GiottoVisuals,spatInSituPlotDensity)
 importFrom(GiottoVisuals,spatInSituPlotHex)

diff --git a/NEWS.md b/NEWS.md
@@ -1,3 +1,13 @@
+
+# Giotto 4.0.6 (2024/05/13)
+
+## Enhancements
+* New `interpolateFeature()` for kriging interpolation of values
+
+
+
+
+
 # Giotto 4.0.5 (2024/03/12)
 
 ## Bug fixes

diff --git a/R/auxiliary_giotto.R b/R/auxiliary_giotto.R
@@ -115,9 +115,9 @@ filterDistributions <- function(gobject,
                                 fill_color = 'lightblue',
                                 scale_axis = 'identity',
                                 axis_offset = 0,
-                                show_plot = NA,
-                                return_plot = NA,
-                                save_plot = NA,
+                                show_plot = NULL,
+                                return_plot = NULL,
+                                save_plot = NULL,
                                 save_param =  list(),
                                 default_save_name = 'filterDistributions') {
 
@@ -281,7 +281,7 @@ filterCombinations <- function(gobject,
                                y_axis_offset = 0,
                                show_plot = TRUE,
                                return_plot = FALSE,
-                               save_plot = NA,
+                               save_plot = NULL,
                                save_param =  list(),
                                default_save_name = 'filterCombinations') {
 
@@ -526,18 +526,22 @@ filterGiotto = function(gobject,
 
   # update cell metadata
   if(isTRUE(tag_cells)) {
-    cell_meta = get_cell_metadata(gobject = gobject, copy_obj = TRUE)
+    cell_meta = getCellMetadata(gobject = gobject, copy_obj = TRUE)
     cell_meta[][, c(tag_cell_name) := ifelse(cell_ID %in% selected_cell_ids, 0, 1)]
-    gobject = set_cell_metadata(gobject = gobject, metadata = cell_meta)
+    gobject = setCellMetadata(
+        gobject = gobject, x = cell_meta, initialize = FALSE
+    )
 
     # set selected cells back to all cells
     selected_cell_ids = names(filter_index_cells)
   }
 
   if(isTRUE(tag_feats)) {
-    feat_meta = get_feature_metadata(gobject = gobject, copy_obj = TRUE)
+    feat_meta = getFeatureMetadata(gobject = gobject, copy_obj = TRUE)
     feat_meta[][, c(tag_feats_name) := ifelse(feat_ID %in% selected_feat_ids, 0, 1)]
-    gobject = set_feature_metadata(gobject = gobject, metadata = feat_meta)
+    gobject = setFeatureMetadata(
+        gobject = gobject, x = feat_meta, initialize = FALSE
+    )
 
     # set selected feats back to all feats
     selected_feat_ids = names(filter_index_feats)
@@ -1053,11 +1057,13 @@ adjustGiottoMatrix <- function(gobject,
                                     feat_type = feat_type)
 
   # metadata
-  cell_metadata = get_cell_metadata(gobject,
-                                    feat_type = feat_type,
-                                    spat_unit = spat_unit,
-                                    output = 'data.table',
-                                    copy_obj = TRUE)
+  cell_metadata = getCellMetadata(
+      gobject,
+      feat_type = feat_type,
+      spat_unit = spat_unit,
+      output = 'data.table',
+      copy_obj = TRUE
+  )
 
   if(!is.null(batch_columns)) {
     if(!all(batch_columns %in% colnames(cell_metadata))) {
@@ -1254,11 +1260,14 @@ addFeatStatistics <- function(gobject,
 
   # expression values to be used
   expression_values = match.arg(expression_values, unique(c('normalized', 'scaled', 'custom', expression_values)))
-  expr_data = get_expression_values(gobject = gobject,
-                                    spat_unit = spat_unit,
-                                    feat_type = feat_type,
-                                    values = expression_values,
-                                    output = 'exprObj')
+  expr_data <- getExpression(
+      gobject = gobject,
+      spat_unit = spat_unit,
+      feat_type = feat_type,
+      values = expression_values,
+      output = 'exprObj',
+      set_defaults = FALSE
+  )
 
   # calculate stats
   feat_stats = data.table::data.table(feats = rownames(expr_data[]),
@@ -1277,11 +1286,14 @@ addFeatStatistics <- function(gobject,
   if(return_gobject == TRUE) {
 
     # remove previous statistics
-    feat_metadata = get_feature_metadata(gobject,
-                                         spat_unit = spat_unit,
-                                         feat_type = feat_type,
-                                         output = 'featMetaObj',
-                                         copy_obj = TRUE)
+      feat_metadata <- getFeatureMetadata(
+          gobject,
+          spat_unit = spat_unit,
+          feat_type = feat_type,
+          output = 'featMetaObj',
+          copy_obj = TRUE,
+          set_defaults = FALSE
+      )
 
     if(isS4(expr_data)) {
       if(!identical(expr_data@provenance, feat_metadata@provenance)) {
@@ -1384,11 +1396,14 @@ addCellStatistics <- function(gobject,
 
   # expression values to be used
   expression_values = match.arg(expression_values, unique(c('normalized', 'scaled', 'custom', expression_values)))
-  expr_data = get_expression_values(gobject = gobject,
-                                    spat_unit = spat_unit,
-                                    feat_type = feat_type,
-                                    values = expression_values,
-                                    output = 'exprObj')
+  expr_data <- getExpression(
+      gobject = gobject,
+      spat_unit = spat_unit,
+      feat_type = feat_type,
+      values = expression_values,
+      output = 'exprObj',
+      set_defaults = FALSE
+  )
 
   # calculate stats
 
@@ -1400,11 +1415,14 @@ addCellStatistics <- function(gobject,
   if(return_gobject == TRUE) {
 
     # remove previous statistics
-    cell_metadata = get_cell_metadata(gobject,
-                                      spat_unit = spat_unit,
-                                      feat_type = feat_type,
-                                      output = 'cellMetaObj',
-                                      copy_obj = TRUE)
+      cell_metadata = getCellMetadata(
+          gobject,
+          spat_unit = spat_unit,
+          feat_type = feat_type,
+          output = 'cellMetaObj',
+          copy_obj = TRUE,
+          set_defaults = FALSE
+      )
 
     if(isS4(expr_data)) {
       if(!identical(expr_data@provenance, cell_metadata@provenance)) {