Merge pull request #1022 from jiajic/suite_dev

chore: remove some deprecated functions and remove or shift dependencies to modules

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: Giotto
 Title: Spatial Single-Cell Transcriptomics Toolbox
-Version: 4.1.1
+Version: 4.1.2
 Authors@R: c(
 	person("Ruben", "Dries", email = "rubendries@gmail.com",
 		 role = c("aut", "cre"), comment = c(ORCID = "0000-0001-7650-7754")),
@@ -36,18 +36,14 @@ Imports:
     BiocParallel,
     BiocSingular,
     checkmate,
-    cowplot (>= 0.9.4),
     data.table (>= 1.12.2),
     dbscan (>= 1.1-3),
     ggplot2 (>= 3.1.1),
-    GiottoUtils (>= 0.1.9),
-    GiottoVisuals (>= 0.2.4),
+    GiottoUtils (>= 0.1.12),
+    GiottoVisuals (>= 0.2.5),
     igraph (>= 1.2.4.1),
-    jsonlite,
     Matrix (>= 1.6-2),
     MatrixGenerics,
-    progressr,
-    reshape2,
     reticulate (>= 1.25),
     scales (>= 1.0.0),
     sparseMatrixStats,

NAMESPACE

@@ -14,7 +14,6 @@ export("prov<-")
 export("sankeyLabel<-")
 export("sankeyRelate<-")
 export("spatUnit<-")
-export(PAGEEnrich)
 export(activeFeatType)
 export(activeSpatUnit)
 export(addCellIntMetadata)
@@ -138,7 +137,6 @@ export(createSpatLocsObj)
 export(createSpatNetObj)
 export(createSpatialDefaultGrid)
 export(createSpatialDelaunayNetwork)
-export(createSpatialEnrich)
 export(createSpatialFeaturesKNNnetwork)
 export(createSpatialGenomicsObject)
 export(createSpatialGrid)
@@ -262,10 +260,8 @@ export(giottoToSeuratV4)
 export(giottoToSeuratV5)
 export(giottoToSpatialExperiment)
 export(heatmSpatialCorFeats)
-export(heatmSpatialCorGenes)
 export(hexVertices)
 export(hist)
-export(hyperGeometricEnrich)
 export(identifyTMAcores)
 export(importCosMx)
 export(importVisiumHD)
@@ -339,7 +335,6 @@ export(print.combIcfObject)
 export(print.icfObject)
 export(processGiotto)
 export(prov)
-export(rankEnrich)
 export(rankSpatialCorGroups)
 export(read10xAffineImage)
 export(readCellMetadata)
@@ -375,7 +370,6 @@ export(runGiottoHarmony)
 export(runHyperGeometricEnrich)
 export(runIntegratedUMAP)
 export(runPAGEEnrich)
-export(runPAGEEnrich_OLD)
 export(runPCA)
 export(runPCAprojection)
 export(runPCAprojectionBatch)

NEWS.md

@@ -1,9 +1,27 @@
 
+# Giotto 4.1.2
+
+## Breaking changes
+* remove deprecated `PAGEEnrich()`. Use `runPAGEEnrich()` instead
+* remove deprecated `rankEnrich()`. Use `runRankEnrich()` instead
+* remove deprecated `hyperGeometricEnrich()`. Use `runHyperGeometricEnrich()` instead
+* remove deprecated `createSpatialEnrich()`. Use `runSpatialEnrich()` instead
+* remove deprecated `heatmSpatialCorGenes()`. Use `heatmSpatialCorFeats()` instead
+* remove deprecated `runPAGEEnrich_OLD()`. Use `runPAGEEnrich()` instead
+
+## Changes
+* `limma`, `plotly`, and `Rtsne` moved to Suggests
+* move `progressr` and `jsonlite` dependencies to GiottoUtils v0.1.12
+* remove `reshape2` dependency.
+
 # Giotto 4.1.1
 
 ## Bug fixes
 * Allow `giottoInstructions` passing for Xenium convenience functions
 
+## Changes
+* Deprecate `screePlot()` `name` in favor of `dim_reduction_name` param
+
 
 # Giotto 4.1.0 (2024/07/31)
 

R/ONTraC_wrapper.R

@@ -398,7 +398,7 @@ plotNicheClusterConnectivity <- function( # nolint: object_name_linter.
   )
   gpl <- gpl + ggraph::scale_edge_alpha(range = c(0.1, 1))
   gpl <- gpl + ggraph::scale_edge_colour_gradientn(
-    colours = RColorBrewer::brewer.pal(9, "Reds"),
+    colours = getColors("Reds", 9, src = "RColorBrewer"),
     name = "Value"
   )
 
@@ -764,4 +764,4 @@ plotCellTypeNTScore <- function(gobject, # nolint: object_name_linter.
     save_param = save_param,
     else_return = NULL
   ))
-}
+}

R/auxiliary_giotto.R

@@ -933,19 +933,12 @@ filterGiotto <- function(
     )
 
     ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
-    gobject <- set_expression_values(
-        gobject = gobject,
-        values = norm_expr
-    )
-
-    gobject <- set_expression_values(
-        gobject = gobject,
-        values = norm_scaled_expr
-    )
+    gobject <- setGiotto(gobject, norm_expr, initialize = FALSE)
+    gobject <- setGiotto(gobject, norm_scaled_expr, initialize = FALSE)
     ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
 
     ## 6. return Giotto object
-    return(gobject)
+    return(initialize(gobject))
 }
 
 
@@ -991,13 +984,9 @@ filterGiotto <- function(
     )
 
     ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
-    gobject <- set_expression_values(
-        gobject = gobject,
-        values = norm_feats_cells
-    )
+    gobject <- setGiotto(giotto, norm_feats_cells)
     ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
 
-
     return(gobject)
 }
 
@@ -1088,10 +1077,7 @@ filterGiotto <- function(
     )
 
     ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
-    gobject <- set_expression_values(
-        gobject = gobject,
-        values = z
-    )
+    gobject <- setGiotto(gobject, z)
     ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
 
     return(gobject)
@@ -1391,10 +1377,7 @@ adjustGiottoMatrix <- function(
         )
 
         ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
-        gobject <- set_expression_values(
-            gobject = gobject,
-            values = adjusted_matrix
-        )
+        gobject <- setGiotto(gobject, adjusted_matrix)
         ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
 
         ## update parameters used ##
@@ -1456,14 +1439,14 @@ processGiotto <- function(
         adjust_params = list(),
         verbose = TRUE) {
     # filter Giotto
-    if (verbose == TRUE) message("1. start filter step")
+    vmsg(.v = verbose, "1. start filter step")
     if (!inherits(filter_params, "list")) {
         stop("filter_params need to be a list of parameters for filterGiotto")
     }
     gobject <- do.call("filterGiotto", c(gobject = gobject, filter_params))
 
     # normalize Giotto
-    if (verbose == TRUE) message("2. start normalization step")
+    vmsg(.v = verbose, "2. start normalization step")
     if (!inherits(norm_params, "list")) {
         stop("norm_params need to be a list of parameters for normalizeGiotto")
     }
@@ -1623,10 +1606,7 @@ addFeatStatistics <- function(
                 "mean_expr_det"
             ) := NULL]
             ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
-            gobject <- set_feature_metadata(gobject,
-                metadata = feat_metadata,
-                verbose = FALSE
-            )
+            gobject <- setGiotto(gobject, feat_metadata, verbose = FALSE)
             ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
         }
 

R/clustering.R

@@ -1223,8 +1223,8 @@ doSNNCluster <- function(
 #' @param set_seed set seed (default = TRUE)
 #' @param seed_number number for seed
 #' @returns if return_gobject = TRUE: giotto object with new clusters appended to cell metadata
-#' @details The default settings will use dimension reduction results as input. 
-#' Set dim_reduction_to_use = NULL if you want to directly use expression values as input. 
+#' @details The default settings will use dimension reduction results as input.
+#' Set dim_reduction_to_use = NULL if you want to directly use expression values as input.
 #' By providing a feature vector to feats_to_use you can subset the expression matrix.
 #' @seealso  \code{\link[stats]{kmeans}}
 #' @examples
@@ -1254,7 +1254,7 @@ doKmeans <- function(
         return_gobject = TRUE,
         set_seed = TRUE,
         seed_number = 1234) {
-  
+
     # Set feat_type and spat_unit
     spat_unit <- set_default_spat_unit(
         gobject = gobject,
@@ -1276,9 +1276,9 @@ doKmeans <- function(
 
     ## using dimension reduction ##
     if(!is.null(dim_reduction_to_use)) {
-      
+
       # use only available dimensions if dimensions < dimensions_to_use
-      dim_coord <- get_dimReduction(
+      dim_coord <- getDimReduction(
         gobject = gobject,
         spat_unit = spat_unit,
         feat_type = feat_type,
@@ -1287,14 +1287,14 @@ doKmeans <- function(
         name = dim_reduction_name,
         output = "dimObj"
       )
-      
+
       dimensions_to_use <- dimensions_to_use[
         dimensions_to_use %in% seq_len(ncol(dim_coord[]))
       ]
       matrix_to_use <- dim_coord[][, dimensions_to_use]
-      
+
     } else {
-      
+
       ## using original matrix ##
       expr_values <- getExpression(
         gobject = gobject,
@@ -1303,21 +1303,21 @@ doKmeans <- function(
         values = expression_values,
         output = "exprObj"
       )
-      
+
       # subset expression matrix
       if (!is.null(feats_to_use)) {
         expr_values[] <- expr_values[][
           rownames(expr_values[]) %in% feats_to_use,
         ]
       }
-      
+
       # features as columns
       # cells as rows
       matrix_to_use <- t_flex(expr_values[])
-      
+
     }
-    
-    
+
+
     ## distance
     if (distance_method == "original") {
         celldist <- matrix_to_use
@@ -2817,7 +2817,7 @@ getClusterSimilarity <- function(
 
     # correlation matrix
     cormatrix <- cor_flex(x = testmatrix, method = cor)
-    cor_table <- data.table::as.data.table(reshape2::melt(cormatrix))
+    cor_table <- melt_matrix(cormatrix)
     data.table::setnames(
         cor_table,
         old = c("Var1", "Var2"), c("group1", "group2")

R/convenience_cosmx.R

@@ -723,8 +723,8 @@ setMethod("$<-", signature("CosmxReader"), function(x, name, value) {
     )
 
     fovs <- fovs %null% .cosmx_imgname_fovparser(path) # ALL if NULL
-    progressr::with_progress({
-        p <- progressr::progressor(along = fovs)
+    with_pbar({
+        p <- pbar(along = fovs)
 
         gpolys <- lapply(fovs, function(f) {
             segfile <- Sys.glob(paths = sprintf("%s/*F%03d*", path, f))
@@ -925,8 +925,8 @@ setMethod("$<-", signature("CosmxReader"), function(x, name, value) {
     fovs <- fovs %null% .cosmx_imgname_fovparser(path) # ALL if NULL
     verbose <- verbose %null% TRUE
 
-    progressr::with_progress({
-        p <- progressr::progressor(along = fovs)
+    with_pbar({
+        p <- pbar(along = fovs)
 
         gimg_list <- lapply(fovs, function(f) {
             imgfile <- Sys.glob(paths = sprintf("%s/*F%03d*", path, f))
@@ -1645,7 +1645,7 @@ createGiottoCosMxObject <- function(
         provenance = "cell_agg"
     )
 
-    cosmx_gobject <- set_expression_values(cosmx_gobject, values = s4_expr)
+    cosmx_gobject <- setGiotto(cosmx_gobject, s4_expr)
 
     # Add spatial locations
     if (isTRUE(verbose)) wrap_msg(
@@ -1669,9 +1669,8 @@ createGiottoCosMxObject <- function(
         provenance = "cell_agg"
     )
 
-    cosmx_gobject <- set_spatial_locations(cosmx_gobject, spatlocs = locsObj)
-    cosmx_gobject <- set_spatial_locations(cosmx_gobject,
-                                           spatlocs = locsObj_fov)
+    cosmx_gobject <- setGiotto(cosmx_gobject, locsObj, initialize = FALSE)
+    cosmx_gobject <- setGiotto(cosmx_gobject, locsObj_fov, initialize = FALSE)
 
     # initialize cell and feat IDs and metadata slots for 'cell_agg' spat_unit
     agg_cell_ID <- colnames(s4_expr[])

R/convenience_general.R

@@ -656,7 +656,7 @@ addVisiumPolygons <- function(gobject,
         return(NULL)
     }
 
-    json_scalefactors <- jsonlite::read_json(json_path)
+    json_scalefactors <- read_json(json_path)
 
     # Intial assertion that json dimensions are appropriate
     checkmate::assert_list(

R/convenience_visiumHD.R

@@ -746,7 +746,7 @@ setMethod("$<-", signature("VisiumHDReader"), function(x, name, value) {
     json_path = file.path(path, 'scalefactors_json.json')
     checkmate::assert_file_exists(json_path)
 
-    json_scalefactors <- jsonlite::read_json(json_path)
+    json_scalefactors <- read_json(json_path)
 
     expected_json_names <- c(
         "regist_target_img_scalef", # NEW as of 2023

R/convenience_xenium.R

@@ -193,7 +193,7 @@ setMethod(
         # decide micron scaling
         if (length(obj@micron) == 0) { # if no value already set
             if (!is.null(experiment_info_path)) {
-                obj@micron <- jsonlite::fromJSON(
+                obj@micron <- fromJSON(
                     experiment_info_path)$pixel_size
             } else {
                 warning(wrap_txt("No .xenium file found.
@@ -914,7 +914,7 @@ importXenium <- function(
     gene_ids <- match.arg(gene_ids, c("symbols", "ensembl"))
 
     # tested on v1.6
-    j <- jsonlite::fromJSON(path)
+    j <- fromJSON(path)
     # j$metadata # dataset meta
     # j$payload # main content
     # j$payload$chemistry # panel chemistry used
@@ -1102,8 +1102,8 @@ importXenium <- function(
     # micron
     checkmate::assert_numeric(micron)
 
-    progressr::with_progress({
-        p <- progressr::progressor(along = path)
+    with_pbar({
+        p <- pbar(along = path)
 
         gimg_list <- lapply(seq_along(path), function(img_i) {
             gimg <- .xenium_image_single(