Merge pull request #817 from jiajic/suite_modular

Small changes and version bump

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: Giotto
 Title: Spatial Single-Cell Transcriptomics Toolbox
-Version: 3.3.2
+Version: 4.0.0
 Authors@R: c(
 	person("Ruben", "Dries", email = "[email protected]",
 		 role = c("aut", "cre")),

NEWS.md

@@ -1,6 +1,7 @@
-# Giotto Suite 3.3.2 (Release TBD)
+# Giotto Suite 4.0.0 2023*11*29)
 
 ## Breaking Changes
+* Update to modular package organization with the main packages being `GiottoUtils`, `GiottoClass`, `GiottoVisuals`, and `Giotto` as the analytical umbrella package.
 
 ## Added
 
@@ -15,7 +16,6 @@
 
 ## Changes
 
-* Improved performance of gefToGiotto()
 
 
 # Giotto Suite 3.3.1 (2023*08*02)

R/differential_expression.R

@@ -38,7 +38,7 @@ findScranMarkers <- function(gobject,
                              group_1_name = NULL,
                              group_2 = NULL,
                              group_2_name = NULL,
-                             verbose = FALSE,
+                             verbose = TRUE,
                              ...) {
 
 
@@ -47,10 +47,12 @@ findScranMarkers <- function(gobject,
 
 
   # print message with information #
-  if(verbose) wrap_msg("using 'Scran' to detect marker genes. If used in published research, please cite:
+  if(isTRUE(verbose)) {
+  wrap_msg("Using 'Scran' to detect marker genes. If used in published research, please cite:
   Lun ATL, McCarthy DJ, Marioni JC (2016).
   'A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor.'
-  F1000Res., 5, 2122. doi: 10.12688/f1000research.9501.2. ")
+  F1000Res., 5, 2122. doi: 10.12688/f1000research.9501.2.")
+  }
 
 
   # Set feat_type and spat_unit

R/dimension_reduction.R

@@ -688,7 +688,7 @@ runPCA_BiocSingular_irlba_projection = function(x,
 #' @param feat_type feature type
 #' @param expression_values expression values to use
 #' @param reduction cells or genes
-#' @param random_subset random subset to perform PCA on
+#' @param random_subset numeric. random subset to perform PCA on
 #' @param name arbitrary name for PCA run
 #' @param feats_to_use subset of features to use for PCA
 #' @param return_gobject boolean: return giotto object (default = TRUE)