Default parameters updated

R/loadData.R

@@ -1151,19 +1151,19 @@ NULL
 #'   (\code{sc.min.mean.counts}). \code{TRUE} by default. 
 #' @param sc.min.mean.counts Minimum non-zero average counts per cluster to
 #'   filter genes. 1 by default. 
-#' @param sc.n.genes.per.cluster Top n genes with the highest logFC per cluster. 
-#'   300 by default. See Details section for more details. 
+#' @param sc.n.genes.per.cluster Top n genes with the highest logFC per cluster
+#'   (300 by default). See Details section for more details. 
 #' @param top.n.genes Maximum number of genes used for downstream steps (2000 
 #'   by default). In case the number of genes after filtering is greater than 
 #'   \code{top.n.genes}, these genes will be set according to 
 #'   variability across the whole single-cell dataset. 
-#' @param sc.min.counts Minimum gene counts to filter (0 by default; single-cell
+#' @param sc.min.counts Minimum gene counts to filter (1 by default; single-cell
 #'   RNA-seq data).
-#' @param sc.min.cells Minimum of cells with more than \code{min.counts} (0 by
+#' @param sc.min.cells Minimum of cells with more than \code{min.counts} (1 by
 #'   default; single-cell RNA-seq data).
-#' @param st.min.counts Minimum gene counts to filter (0 by default; spatial
+#' @param st.min.counts Minimum gene counts to filter (1 by default; spatial
 #'   transcriptomics data).
-#' @param st.min.spots Minimum of cells with more than \code{min.counts} (0 by
+#' @param st.min.spots Minimum of cells with more than \code{min.counts} (1 by
 #'   default; spatial transcriptomics data).
 #' @param st.n.slides Minimum number of slides
 #'   (\code{\linkS4class{SpatialExperiment}} objects) in which a gene has to be
@@ -1172,7 +1172,7 @@ NULL
 #'   not present in at least \code{st.n.slides} will be discarded. If no
 #'   filtering is desired, set \code{st.n.slides = 1}.
 #' @param shared.genes If set to \code{TRUE}, only genes present in both the
-#'   isngle-cell and spatial transcriptomics data will be retained for further
+#'   single-cell and spatial transcriptomics data will be retained for further
 #'   processing (\code{TRUE} by default).
 #' @param sc.name.dataset.h5 Name of the data set if HDF5 file is provided for
 #'   single-cell RNA-seq data.
@@ -1274,10 +1274,10 @@ createSpatialDDLSobject <- function(
     sc.min.mean.counts = 1, 
     sc.n.genes.per.cluster = 300,
     top.n.genes = 2000,
-    sc.min.counts = 0,
-    sc.min.cells = 0,
-    st.min.counts = 0,
-    st.min.spots = 0,
+    sc.min.counts = 1,
+    sc.min.cells = 1,
+    st.min.counts = 1,
+    st.min.spots = 1,
     st.n.slides = 3,
     shared.genes = TRUE,
     sc.name.dataset.h5 = NULL, 

R/simMixedSpots.R

@@ -46,14 +46,14 @@ NULL
 #'   single-cell profiles.
 #' @param n.cells Specifies the number of cells to be randomly selected and
 #'   combined to generate the simulated mixed profiles. By default, it is set to
-#'   100. It controls the level of noise present in the simulated data, as it
+#'   50 It controls the level of noise present in the simulated data, as it
 #'   determines how many single-cell profiles will be combined to produce each
 #'   spot.
 #' @param train.freq.cells Proportion of cells used to simulate training mixed
-#'   transcriptional profiles (2/3 by default).
+#'   transcriptional profiles (3/4 by default).
 #' @param train.freq.spots Proportion of mixed transcriptional profiles to be
 #'   used for training, relative to the total number of simulated spots
-#'   (\code{num.sim.spots}). The default value is 2/3.
+#'   (\code{num.sim.spots}). The default value is 3/4.
 #' @param proportion.method Vector with three elements that controls the
 #'   proportion of simulated proportions generated by each method: random
 #'   sampling of a Dirichlet distribution, "pure" spots (1 cell type), and spots
@@ -127,8 +127,8 @@ genMixedCellProp <- function(
   cell.type.column,
   num.sim.spots,
   n.cells = 50,
-  train.freq.cells = 2/3,
-  train.freq.spots = 2/3,
+  train.freq.cells = 3/4,
+  train.freq.spots = 3/4,
   proportion.method = c(0, 0, 1),
   prob.sparity = 1,
   min.zero.prop = NULL,