Added NEWS file. Minor text edits to clustsignal function.

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: clustSIGNAL
 Type: Package
 Title: clustSIGNAL: a spatial clustering method
-Version: 0.99.3
+Version: 0.99.4
 Authors@R: c(
     person("Pratibha", "Panwar", email = "[email protected]", 
     role = c("cre", "aut", "ctb"), comment = c(ORCID = "0000-0002-7437-7084")),

NEWS.md

@@ -0,0 +1,13 @@
+## clustSIGNAL v0.99.4 (2024-11-28)
+* Corrected character check for output format type.
+
+## clustSIGNAL v0.00.3 (2024-10-31)
+* Clustering parameter options added to package
+* Initial and final clustering steps are now in separate functions
+* Test units added to the package
+
+## clustSIGNAL v0.00.2 (2024-10-08)
+* Updated parallel runs in smoothing function for faster runs
+
+## clustSIGNAL v0.99.0 (2024-09-19)
+* Submitted to Bioconductor.

R/clustSIGNAL.R

@@ -87,8 +87,8 @@ clustSIGNAL <- function (spe, samples, cells, dimRed = "None", batch = FALSE,
         stop("NN cannot be less than 1.")
     } else if (!(kernel %in% c("G", "E"))) {
         stop("Invalid kernel type.")
-    } else if (!(outputs %in% c('c', 'n', 's', 'a'))) {
-        stop("Invalid output type.")}
+    } else if (!(outputs %in% c('c', 'a'))) {
+        stop("Invalid character for output type.")}
 
     if (dimRed == "None") {
         show(paste("Calculating PCA. Time", format(Sys.time(),'%H:%M:%S')))
@@ -99,7 +99,6 @@ clustSIGNAL <- function (spe, samples, cells, dimRed = "None", batch = FALSE,
     show(paste("clustSIGNAL run started. Time", format(Sys.time(),'%H:%M:%S')))
 
     # Non-spatial clustering to identify initial cluster groups
-    # reclust should always be FALSE here
     spe <- p1_clustering(spe, dimRed, batch, batch_by, clustParams)
     # Neighborhood detection, and sorting if sort = TRUE
     outReg <- neighbourDetect(spe, samples, NN, cells, sort)
@@ -108,7 +107,6 @@ clustSIGNAL <- function (spe, samples, cells, dimRed = "None", batch = FALSE,
     # Weighted smoothing guided by neighbourhood entropy
     spe <- adaptiveSmoothing(spe, outReg$nnCells, NN, kernel, spread, threads)
     # Non-spatial clustering of adaptively smoothed expression
-    # reclust should always be TRUE here
     spe <- p2_clustering(spe, batch, batch_by, clustParams)
 
     cluster_df <- data.frame("Cells" = spe[[cells]],