@@ -534,7 +534,7 @@ setMethod("recursiveSplitCell",

       verbose = FALSE,

       reorder = reorder)

     currentK <- length(unique(celdaClusters(modelInitial)$z)) + 1

-    overallZ <- celdaClusters(modelInitial)$z

+    overallZ <- as.integer(celdaClusters(modelInitial)$z)

     resList <- list(modelInitial)

     while (currentK <= maxK) {

       # previousY <- overallY

@@ -574,14 +574,14 @@ setMethod("recursiveSplitCell",

       # If the number of clusters is still "currentK", then keep the

       # reordering, otherwise keep the previous configuration

       if (length(unique(celdaClusters(tempModel)$z)) == currentK) {

-        overallZ <- celdaClusters(tempModel)$z

+        overallZ <- as.integer(celdaClusters(tempModel)$z)

       } else {

         overallZ <- tempSplit$z

         ll <- .logLikelihoodcelda_CG(

           counts,

           s,

           overallZ,

-          celdaClusters(tempModel)$y,

+          as.integer(celdaClusters(tempModel)$y),

           currentK,

           L,

           alpha,

@@ -590,7 +590,7 @@ setMethod("recursiveSplitCell",

           gamma

         )

         tempModel <- methods::new("celda_CG",

-          clusters = list(z = overallZ, y = celdaClusters(tempModel)$y),

+          clusters = list(z = overallZ, y = as.integer(celdaClusters(tempModel)$y)),

           params = list(

             K = as.integer(currentK),

             L = as.integer(L),

@@ -670,7 +670,7 @@ setMethod("recursiveSplitCell",

       reorder = reorder

     )

     currentK <- length(unique(celdaClusters(modelInitial)$z)) + 1

-    overallZ <- celdaClusters(modelInitial)$z

+    overallZ <- as.integer(celdaClusters(modelInitial)$z)

     ll <- .logLikelihoodcelda_C(

       counts, s, overallZ, currentK,

       alpha, beta

@@ -707,7 +707,7 @@ setMethod("recursiveSplitCell",

       # Handle rare cases where a population has no cells after running

       # the model

       if (length(unique(celdaClusters(tempModel)$z)) == currentK) {

-        overallZ <- celdaClusters(tempModel)$z

+        overallZ <- as.integer(celdaClusters(tempModel)$z)

       } else {

         overallZ <- tempSplit$z

       }

@@ -772,7 +772,7 @@ setMethod("recursiveSplitCell",

       reorder = reorder

     )

     currentK <- length(unique(celdaClusters(modelInitial)$z)) + 1

-    overallZ <- celdaClusters(modelInitial)$z

+    overallZ <- as.integer(celdaClusters(modelInitial)$z)

     resList <- list(modelInitial)

     while (currentK <= maxK) {

       tempSplit <- .singleSplitZ(counts,

@@ -798,7 +798,7 @@ setMethod("recursiveSplitCell",

       )

       if (length(unique(celdaClusters(tempModel)$z)) == currentK) {

-        overallZ <- celdaClusters(tempModel)$z

+        overallZ <- as.integer(celdaClusters(tempModel)$z)

       } else {

         overallZ <- tempSplit$z

         ll <-

@@ -1336,7 +1336,7 @@ setMethod("recursiveSplitModule",

       verbose = FALSE,

       reorder = reorder)

     currentL <- length(unique(celdaClusters(modelInitial)$y)) + 1

-    overallY <- celdaClusters(modelInitial)$y

+    overallY <- as.integer(celdaClusters(modelInitial)$y)

     resList <- list(modelInitial)

     while (currentL <= maxL) {

@@ -1365,7 +1365,7 @@ setMethod("recursiveSplitModule",

         zInit = overallZ,

         reorder = reorder

       )

-      overallY <- celdaClusters(tempModel)$y

+      overallY <- as.integer(celdaClusters(tempModel)$y)

       ## Add new model to results list and increment L

       .logMessages(

@@ -1428,8 +1428,8 @@ setMethod("recursiveSplitModule",

     )

     modelInitial@params$countChecksum <- countChecksum

-    currentL <- length(unique(celdaClusters(modelInitial)$y)) + 1

-    overallY <- celdaClusters(modelInitial)$y

+    currentL <- length(unique(as.integer(celdaClusters(modelInitial)$y))) + 1

+    overallY <- as.integer(celdaClusters(modelInitial)$y)

     ## Decomposed counts for full count matrix

     p <- .cGDecomposeCounts(counts, overallY, currentL)

@@ -1465,7 +1465,7 @@ setMethod("recursiveSplitModule",

         yInit = tempSplit$y,

         reorder = reorder

       )

-      overallY <- celdaClusters(tempModel)$y

+      overallY <- as.integer(celdaClusters(tempModel)$y)

       # Adjust decomposed count matrices

       p <- .cGReDecomposeCounts(counts,

@@ -1543,7 +1543,7 @@ setMethod("recursiveSplitModule",

       nchains = 1,

       verbose = FALSE

     )

-    overallY <- celdaClusters(modelInitial)$y

+    overallY <- as.integer(celdaClusters(modelInitial)$y)

     currentL <- length(unique(overallY)) + 1

     ## Perform splitting for y labels

@@ -1572,7 +1572,7 @@ setMethod("recursiveSplitModule",

         yInit = tempSplit$y,

         reorder = reorder

       )

-      overallY <- celdaClusters(tempModel)$y

+      overallY <- as.integer(celdaClusters(tempModel)$y)

       ## Add new model to results list and increment L

       .logMessages(

@@ -547,7 +547,7 @@ setMethod("recursiveSplitCell",

         beta = beta

       )

       tempModel <- .celda_CG(counts,

-        sampleLabel = s,

+        sampleLabel = sampleLabel,

         K = as.integer(currentK),

         L = as.integer(L),

         yInit = overallY,

@@ -660,7 +660,7 @@ setMethod("recursiveSplitCell",

       logfile = logfile

     )

     modelInitial <- .celda_C(countsY,

-      sampleLabel = s,

+      sampleLabel = sampleLabel,

       K = as.integer(initialK),

       zInitialize = "split",

       nchains = 1,

@@ -691,7 +691,7 @@ setMethod("recursiveSplitCell",

         beta = beta

       )

       tempModel <- .celda_C(countsY,

-        sampleLabel = s,

+        sampleLabel = sampleLabel,

         K = as.integer(currentK),

         nchains = 1,

         zInitialize = "random",

@@ -762,7 +762,7 @@ setMethod("recursiveSplitCell",

       logfile = logfile

     )

     modelInitial <- .celda_C(counts,

-      sampleLabel = s,

+      sampleLabel = sampleLabel,

       K = as.integer(initialK),

       zInitialize = "split",

       nchains = 1,

@@ -784,7 +784,7 @@ setMethod("recursiveSplitCell",

         beta = beta

       )

       tempModel <- .celda_C(counts,

-        sampleLabel = s,

+        sampleLabel = sampleLabel,

         K = as.integer(currentK),

         nchains = 1,

         zInitialize = "random",

@@ -137,14 +137,9 @@

 #' @param doResampling Boolean. If \code{TRUE}, then each cell in the counts

 #' matrix will be resampled according to a multinomial distribution to introduce

 #' noise before calculating perplexity. Default \code{FALSE}.

-#' @param doSubsampling Boolean. If \code{TRUE}, then a subset of cells from

-#' the original counts matrix will be randomly selected. Default \code{TRUE}.

 #' @param numResample Integer. The number of times to resample the counts matrix

-#' for evaluating perplexity if \code{doSubsampling} is set to \code{TRUE}.

+#' for evaluating perplexity if \code{doResampling} is set to \code{TRUE}.

 #' Default \code{5}.

-#' @param numSubsample Integer. The number of cells to sample from the

-#' the counts matrix if \code{doSubsampling} is set to \code{TRUE}. 

-#' Default \code{5000}.

 #' @param verbose Logical. Whether to print log messages. Default TRUE.

 #' @param logfile Character. Messages will be redirected to a file named

 #'  "logfile". If NULL, messages will be printed to stdout.  Default NULL.

@@ -174,9 +169,7 @@ setGeneric("recursiveSplitCell",

         seed = 12345,

         perplexity = TRUE,

         doResampling = FALSE,

-        doSubsampling = TRUE,

         numResample = 5,

-        numSubsample = 5000,

         logfile = NULL,

         verbose = TRUE) {

     standardGeneric("recursiveSplitCell")})

@@ -221,9 +214,7 @@ setMethod("recursiveSplitCell",

         seed = 12345,

         perplexity = TRUE,

         doResampling = FALSE,

-        doSubsampling = TRUE,

         numResample = 5,

-        numSubsample = 5000,

         logfile = NULL,

         verbose = TRUE) {

@@ -263,9 +254,7 @@ setMethod("recursiveSplitCell",

             seed = seed,

             perplexity = perplexity,

             doResampling = doResampling,

-            doSubsampling = doSubsampling,

             numResample = numResample,

-            numSubsample = numSubsample,

             logfile = logfile,

             verbose = verbose)

@@ -335,9 +324,7 @@ setMethod("recursiveSplitCell",

         seed = 12345,

         perplexity = TRUE,

         doResampling = FALSE,

-        doSubsampling = TRUE,

         numResample = 5,

-        numSubsample = 5000,

         logfile = NULL,

         verbose = TRUE) {

@@ -368,9 +355,7 @@ setMethod("recursiveSplitCell",

             seed = seed,

             perplexity = perplexity,

             doResampling = doResampling,

-            doSubsampling = doSubsampling,

             numResample = numResample,

-            numSubsample = numSubsample,

             logfile = logfile,

             verbose = verbose)

@@ -415,9 +400,7 @@ setMethod("recursiveSplitCell",

     seed,

     perplexity,

     doResampling,

-    doSubsampling,

     numResample,

-    numSubsample,

     logfile,

     verbose) {

@@ -436,9 +419,7 @@ setMethod("recursiveSplitCell",

             reorder = reorder,

             perplexity = perplexity,

             doResampling = doResampling,

-            doSubsampling = doSubsampling,

             numResample = numResample,

-            numSubsample = numSubsample,

             logfile = logfile,

             verbose = verbose)

     } else {

@@ -458,9 +439,7 @@ setMethod("recursiveSplitCell",

                 reorder = reorder,

                 perplexity = perplexity,

                 doResampling = doResampling,

-                doSubsampling = doSubsampling,

                 numResample = numResample,

-                numSubsample = numSubsample,

                 logfile = logfile,

                 verbose = verbose)

         )

@@ -484,9 +463,7 @@ setMethod("recursiveSplitCell",

                                reorder,

                                perplexity,

                                doResampling,

-                               doSubsampling,

                                numResample,

-                               numSubsample,

                                logfile,

                                verbose) {

@@ -890,9 +867,7 @@ setMethod("recursiveSplitCell",

     )

     celdaRes <- resamplePerplexity(counts, celdaRes,

                                    doResampling = doResampling,

-                                   doSubsampling = doSubsampling,

-                                   numResample = numResample,

-                                   numSubsample = numSubsample)

+                                   numResample = numResample)

   }

   endTime <- Sys.time()

   .logMessages(

@@ -973,14 +948,9 @@ setMethod("recursiveSplitCell",

 #' @param doResampling Boolean. If \code{TRUE}, then each cell in the counts

 #' matrix will be resampled according to a multinomial distribution to introduce

 #' noise before calculating perplexity. Default \code{FALSE}.

-#' @param doSubsampling Boolean. If \code{TRUE}, then a subset of cells from

-#' the original counts matrix will be randomly selected. Default \code{TRUE}.

 #' @param numResample Integer. The number of times to resample the counts matrix

-#' for evaluating perplexity if \code{doSubsampling} is set to \code{TRUE}.

+#' for evaluating perplexity if \code{doResampling} is set to \code{TRUE}.

 #' Default \code{5}.

-#' @param numSubsample Integer. The number of cells to sample from the

-#' the counts matrix if \code{doSubsampling} is set to \code{TRUE}. 

-#' Default \code{5000}.

 #' @param verbose Logical. Whether to print log messages. Default TRUE.

 #' @param logfile Character. Messages will be redirected to a file named

 #'  "logfile". If NULL, messages will be printed to stdout.  Default NULL.

@@ -1010,9 +980,7 @@ setGeneric("recursiveSplitModule",

         seed = 12345,

         perplexity = TRUE,

         doResampling = FALSE,

-        doSubsampling = TRUE,

         numResample = 5,

-        numSubsample = 5000,

         verbose = TRUE,

         logfile = NULL) {

     standardGeneric("recursiveSplitModule")})

@@ -1050,9 +1018,7 @@ setMethod("recursiveSplitModule",

         seed = 12345,

         perplexity = TRUE,

         doResampling = FALSE,

-        doSubsampling = TRUE,

         numResample = 5,

-        numSubsample = 5000,

         verbose = TRUE,

         logfile = NULL) {

@@ -1092,9 +1058,7 @@ setMethod("recursiveSplitModule",

             seed = seed,

             perplexity = perplexity,

             doResampling = doResampling,

-            doSubsampling = doSubsampling,

             numResample = numResample,

-            numSubsample = numSubsample,

             verbose = verbose,

             logfile = logfile)

@@ -1157,9 +1121,7 @@ setMethod("recursiveSplitModule",

         seed = 12345,

         perplexity = TRUE,

         doResampling = FALSE,

-        doSubsampling = TRUE,

         numResample = 5,

-        numSubsample = 5000,

         verbose = TRUE,

         logfile = NULL) {

@@ -1190,9 +1152,7 @@ setMethod("recursiveSplitModule",

             seed = seed,

             perplexity = perplexity,

             doResampling = doResampling,

-            doSubsampling = doSubsampling,

             numResample = numResample,

-            numSubsample = numSubsample,

             verbose = verbose,

             logfile = logfile)

@@ -1237,9 +1197,7 @@ setMethod("recursiveSplitModule",

     seed,

     perplexity,

     doResampling,

-    doSubsampling,

     numResample,

-    numSubsample,

     verbose,

     logfile) {

@@ -1261,9 +1219,7 @@ setMethod("recursiveSplitModule",

             verbose = verbose,

             logfile = logfile,

             doResampling = doResampling,

-            doSubsampling = doSubsampling,

-            numResample = numResample,

-            numSubsample = numSubsample)

+            numResample = numResample)

     } else {

         with_seed(seed,

             celdaList <- .recursiveSplitModule(

@@ -1283,9 +1239,7 @@ setMethod("recursiveSplitModule",

                 verbose = verbose,

                 logfile = logfile,

                 doResampling = doResampling,

-                doSubsampling = doSubsampling,

-                numResample = numResample,

-                numSubsample = numSubsample)

+                numResample = numResample)

         )

     }

@@ -1309,9 +1263,7 @@ setMethod("recursiveSplitModule",

                                  verbose = TRUE,

                                  logfile = NULL,

                                  doResampling = FALSE,

-                                 doSubsampling = TRUE,

-                                 numResample = 5,

-                                 numSubsample = 5000) {

+                                 numResample = 5) {

   .logMessages(paste(rep("=", 50), collapse = ""),

     logfile = logfile,

@@ -1673,9 +1625,7 @@ setMethod("recursiveSplitModule",

     )

     celdaRes <- resamplePerplexity(counts, celdaRes,

                                    doResampling = doResampling,

-                                   doSubsampling = doSubsampling,

-                                   numResample = numResample,

-                                   numSubsample = numSubsample)

+                                   numResample = numResample)

   }

   endTime <- Sys.time()

@@ -134,6 +134,17 @@

 #' @param perplexity Logical. Whether to calculate perplexity for each model.

 #'  If FALSE, then perplexity can be calculated later with

 #'  \link{resamplePerplexity}. Default TRUE.

+#' @param doResampling Boolean. If \code{TRUE}, then each cell in the counts

+#' matrix will be resampled according to a multinomial distribution to introduce

+#' noise before calculating perplexity. Default \code{FALSE}.

+#' @param doSubsampling Boolean. If \code{TRUE}, then a subset of cells from

+#' the original counts matrix will be randomly selected. Default \code{TRUE}.

+#' @param numResample Integer. The number of times to resample the counts matrix

+#' for evaluating perplexity if \code{doSubsampling} is set to \code{TRUE}.

+#' Default \code{5}.

+#' @param numSubsample Integer. The number of cells to sample from the

+#' the counts matrix if \code{doSubsampling} is set to \code{TRUE}. 

+#' Default \code{5000}.

 #' @param verbose Logical. Whether to print log messages. Default TRUE.

 #' @param logfile Character. Messages will be redirected to a file named

 #'  "logfile". If NULL, messages will be printed to stdout.  Default NULL.

@@ -162,6 +173,10 @@ setGeneric("recursiveSplitCell",

         reorder = TRUE,

         seed = 12345,

         perplexity = TRUE,

+        doResampling = FALSE,

+        doSubsampling = TRUE,

+        numResample = 5,

+        numSubsample = 5000,

         logfile = NULL,

         verbose = TRUE) {

     standardGeneric("recursiveSplitCell")})

@@ -205,6 +220,10 @@ setMethod("recursiveSplitCell",

         reorder = TRUE,

         seed = 12345,

         perplexity = TRUE,

+        doResampling = FALSE,

+        doSubsampling = TRUE,

+        numResample = 5,

+        numSubsample = 5000,

         logfile = NULL,

         verbose = TRUE) {

@@ -243,6 +262,10 @@ setMethod("recursiveSplitCell",

             reorder = reorder,

             seed = seed,

             perplexity = perplexity,

+            doResampling = doResampling,

+            doSubsampling = doSubsampling,

+            numResample = numResample,

+            numSubsample = numSubsample,

             logfile = logfile,

             verbose = verbose)

@@ -311,6 +334,10 @@ setMethod("recursiveSplitCell",

         reorder = TRUE,

         seed = 12345,

         perplexity = TRUE,

+        doResampling = FALSE,

+        doSubsampling = TRUE,

+        numResample = 5,

+        numSubsample = 5000,

         logfile = NULL,

         verbose = TRUE) {

@@ -340,6 +367,10 @@ setMethod("recursiveSplitCell",

             reorder = reorder,

             seed = seed,

             perplexity = perplexity,

+            doResampling = doResampling,

+            doSubsampling = doSubsampling,

+            numResample = numResample,

+            numSubsample = numSubsample,

             logfile = logfile,

             verbose = verbose)

@@ -383,6 +414,10 @@ setMethod("recursiveSplitCell",

     reorder,

     seed,

     perplexity,

+    doResampling,

+    doSubsampling,

+    numResample,

+    numSubsample,

     logfile,

     verbose) {

@@ -400,6 +435,10 @@ setMethod("recursiveSplitCell",

             minCell = minCell,

             reorder = reorder,

             perplexity = perplexity,

+            doResampling = doResampling,

+            doSubsampling = doSubsampling,

+            numResample = numResample,

+            numSubsample = numSubsample,

             logfile = logfile,

             verbose = verbose)

     } else {

@@ -418,6 +457,10 @@ setMethod("recursiveSplitCell",

                 minCell = minCell,

                 reorder = reorder,

                 perplexity = perplexity,

+                doResampling = doResampling,

+                doSubsampling = doSubsampling,

+                numResample = numResample,

+                numSubsample = numSubsample,

                 logfile = logfile,

                 verbose = verbose)

         )

@@ -440,6 +483,10 @@ setMethod("recursiveSplitCell",

                                minCell,

                                reorder,

                                perplexity,

+                               doResampling,

+                               doSubsampling,

+                               numResample,

+                               numSubsample,

                                logfile,

                                verbose) {

@@ -841,7 +888,11 @@ setMethod("recursiveSplitCell",

       verbose = verbose,

       logfile = NULL

     )

-    celdaRes <- resamplePerplexity(counts, celdaRes)

+    celdaRes <- resamplePerplexity(counts, celdaRes,

+                                   doResampling = doResampling,

+                                   doSubsampling = doSubsampling,

+                                   numResample = numResample,

+                                   numSubsample = numSubsample)

   }

   endTime <- Sys.time()

   .logMessages(

@@ -918,7 +969,18 @@ setMethod("recursiveSplitCell",

 #'  \link[withr]{with_seed} are made.

 #' @param perplexity Logical. Whether to calculate perplexity for each model.

 #'  If FALSE, then perplexity can be calculated later with

-#'  \link{resamplePerplexity}. Default TRUE.

+#'  \link{resamplePerplexity}. Default \code{TRUE}.

+#' @param doResampling Boolean. If \code{TRUE}, then each cell in the counts

+#' matrix will be resampled according to a multinomial distribution to introduce

+#' noise before calculating perplexity. Default \code{FALSE}.

+#' @param doSubsampling Boolean. If \code{TRUE}, then a subset of cells from

+#' the original counts matrix will be randomly selected. Default \code{TRUE}.

+#' @param numResample Integer. The number of times to resample the counts matrix

+#' for evaluating perplexity if \code{doSubsampling} is set to \code{TRUE}.

+#' Default \code{5}.

+#' @param numSubsample Integer. The number of cells to sample from the

+#' the counts matrix if \code{doSubsampling} is set to \code{TRUE}. 

+#' Default \code{5000}.

 #' @param verbose Logical. Whether to print log messages. Default TRUE.

 #' @param logfile Character. Messages will be redirected to a file named

 #'  "logfile". If NULL, messages will be printed to stdout.  Default NULL.

@@ -947,6 +1009,10 @@ setGeneric("recursiveSplitModule",

         reorder = TRUE,

         seed = 12345,

         perplexity = TRUE,

+        doResampling = FALSE,

+        doSubsampling = TRUE,

+        numResample = 5,

+        numSubsample = 5000,

         verbose = TRUE,

         logfile = NULL) {

     standardGeneric("recursiveSplitModule")})

@@ -983,6 +1049,10 @@ setMethod("recursiveSplitModule",

         reorder = TRUE,

         seed = 12345,

         perplexity = TRUE,

+        doResampling = FALSE,

+        doSubsampling = TRUE,

+        numResample = 5,

+        numSubsample = 5000,

         verbose = TRUE,

         logfile = NULL) {

@@ -1021,6 +1091,10 @@ setMethod("recursiveSplitModule",

             reorder = reorder,

             seed = seed,

             perplexity = perplexity,

+            doResampling = doResampling,

+            doSubsampling = doSubsampling,

+            numResample = numResample,

+            numSubsample = numSubsample,

             verbose = verbose,

             logfile = logfile)

@@ -1082,6 +1156,10 @@ setMethod("recursiveSplitModule",

         reorder = TRUE,

         seed = 12345,

         perplexity = TRUE,

+        doResampling = FALSE,

+        doSubsampling = TRUE,

+        numResample = 5,

+        numSubsample = 5000,

         verbose = TRUE,

         logfile = NULL) {

@@ -1111,6 +1189,10 @@ setMethod("recursiveSplitModule",

             reorder = reorder,

             seed = seed,

             perplexity = perplexity,

+            doResampling = doResampling,

+            doSubsampling = doSubsampling,

+            numResample = numResample,

+            numSubsample = numSubsample,

             verbose = verbose,

             logfile = logfile)

@@ -1154,6 +1236,10 @@ setMethod("recursiveSplitModule",

     reorder,

     seed,

     perplexity,

+    doResampling,

+    doSubsampling,

+    numResample,

+    numSubsample,

     verbose,

     logfile) {

@@ -1173,7 +1259,11 @@ setMethod("recursiveSplitModule",

             reorder = reorder,

             perplexity = perplexity,

             verbose = verbose,

-            logfile = logfile)

+            logfile = logfile,

+            doResampling = doResampling,

+            doSubsampling = doSubsampling,

+            numResample = numResample,

+            numSubsample = numSubsample)

     } else {

         with_seed(seed,

             celdaList <- .recursiveSplitModule(

@@ -1191,7 +1281,11 @@ setMethod("recursiveSplitModule",

                 reorder = reorder,

                 perplexity = perplexity,

                 verbose = verbose,

-                logfile = logfile)

+                logfile = logfile,

+                doResampling = doResampling,

+                doSubsampling = doSubsampling,

+                numResample = numResample,

+                numSubsample = numSubsample)

         )

     }

@@ -1213,7 +1307,11 @@ setMethod("recursiveSplitModule",

                                  reorder = TRUE,

                                  perplexity = TRUE,

                                  verbose = TRUE,

-                                 logfile = NULL) {

+                                 logfile = NULL,

+                                 doResampling = FALSE,

+                                 doSubsampling = TRUE,

+                                 numResample = 5,

+                                 numSubsample = 5000) {

   .logMessages(paste(rep("=", 50), collapse = ""),

     logfile = logfile,

@@ -1573,7 +1671,11 @@ setMethod("recursiveSplitModule",

       verbose = verbose,

       logfile = NULL

     )

-    celdaRes <- resamplePerplexity(counts, celdaRes)

+    celdaRes <- resamplePerplexity(counts, celdaRes,

+                                   doResampling = doResampling,

+                                   doSubsampling = doSubsampling,

+                                   numResample = numResample,

+                                   numSubsample = numSubsample)

   }

   endTime <- Sys.time()

@@ -496,7 +496,7 @@ setMethod("recursiveSplitCell",

       verbose = verbose,

       logfile = logfile)

     modelInitial <- .celda_CG(counts,

-      sampleLabel = s,

+      sampleLabel = sampleLabel,

       K = as.integer(initialK),

       L = as.integer(L),

       zInitialize = "split",

@@ -1272,7 +1272,7 @@ setMethod("recursiveSplitModule",

       logfile = logfile

     )

     modelInitial <- .celda_CG(counts,

-      sampleLabel = s,

+      sampleLabel = sampleLabel,

       L = initialL,

       K = K,

       zInitialize = "predefined",

@@ -1640,6 +1640,7 @@ setMethod("recursiveSplitModule",

             perplexity = perplexity,

             logfile = logfile,

             verbose = verbose)

+    SummarizedExperiment::colData(sce)$"celda_sample_label" <- sampleLabel

     return(sce)

 }

@@ -1687,5 +1688,6 @@ setMethod("recursiveSplitModule",

             perplexity = perplexity,

             logfile = logfile,

             verbose = verbose)

+    SummarizedExperiment::colData(sce)$"celda_sample_label" <- sampleLabel

     return(sce)

 }

@@ -1549,7 +1549,7 @@ setMethod("recursiveSplitModule",

     )

   }

-  ## Summarize paramters of different models

+  ## Summarize parameters of different models

   logliks <- vapply(resList, function(mod) {

     bestLogLikelihood(mod)

   }, double(1))

@@ -137,7 +137,6 @@

 #' @param verbose Logical. Whether to print log messages. Default TRUE.

 #' @param logfile Character. Messages will be redirected to a file named

 #'  "logfile". If NULL, messages will be printed to stdout.  Default NULL.

-#' @param ... Ignored. Placeholder to prevent check warning.

 #' @return A \linkS4class{SingleCellExperiment} object. Function

 #'  parameter settings and celda model results are stored in the

 #'  \link{metadata} \code{"celda_grid_search"} slot. The models in

@@ -146,7 +145,25 @@

 #' @seealso \link{recursiveSplitModule} for recursive splitting of feature

 #'  modules.

 #' @export

-setGeneric("recursiveSplitCell", function(x, ...) {

+setGeneric("recursiveSplitCell",

+    function(x,

+        useAssay = "counts",

+        altExpName = "featureSubset",

+        sampleLabel = NULL,

+        initialK = 5,

+        maxK = 25,

+        tempL = NULL,

+        yInit = NULL,

+        alpha = 1,

+        beta = 1,

+        delta = 1,

+        gamma = 1,

+        minCell = 3,

+        reorder = TRUE,

+        seed = 12345,

+        perplexity = TRUE,

+        logfile = NULL,

+        verbose = TRUE) {

     standardGeneric("recursiveSplitCell")})

@@ -905,7 +922,6 @@ setMethod("recursiveSplitCell",

 #' @param verbose Logical. Whether to print log messages. Default TRUE.

 #' @param logfile Character. Messages will be redirected to a file named

 #'  "logfile". If NULL, messages will be printed to stdout.  Default NULL.

-#' @param ... Ignored. Placeholder to prevent check warning.

 #' @return A \linkS4class{SingleCellExperiment} object. Function

 #'  parameter settings and celda model results are stored in the

 #'  \link{metadata} \code{"celda_grid_search"} slot. The models in

@@ -914,7 +930,25 @@ setMethod("recursiveSplitCell",

 #' @seealso \code{recursiveSplitCell} for recursive splitting of cell

 #'  populations.

 #' @export

-setGeneric("recursiveSplitModule", function(x, ...) {

+setGeneric("recursiveSplitModule",

+    function(x,

+        useAssay = "counts",

+        altExpName = "featureSubset",

+        initialL = 10,

+        maxL = 100,

+        tempK = 100,

+        zInit = NULL,

+        sampleLabel = NULL,

+        alpha = 1,

+        beta = 1,

+        delta = 1,

+        gamma = 1,

+        minFeature = 3,

+        reorder = TRUE,

+        seed = 12345,

+        perplexity = TRUE,

+        verbose = TRUE,

+        logfile = NULL) {

     standardGeneric("recursiveSplitModule")})

@@ -1343,7 +1343,7 @@ setMethod("recursiveSplitModule",

       verbose = FALSE

     )

     modelInitial@params$countChecksum <- countChecksum

-    

+

     currentL <- length(unique(celdaClusters(modelInitial)$y)) + 1

     overallY <- celdaClusters(modelInitial)$y

@@ -1342,7 +1342,8 @@ setMethod("recursiveSplitModule",

       nchains = 1,

       verbose = FALSE

     )

-

+    modelInitial@params$countChecksum <- countChecksum

+    

     currentL <- length(unique(celdaClusters(modelInitial)$y)) + 1

     overallY <- celdaClusters(modelInitial)$y

@@ -96,23 +96,26 @@

 #'  to use. Default "featureSubset".

 #' @param sampleLabel Vector or factor. Denotes the sample label for each cell

 #'  (column) in the count matrix.

-#' @param initialK Integer. Minimum number of cell populations to try.

+#' @param initialK Integer. Initial number of cell populations to try.

+#' Default \code{5}.

 #' @param maxK Integer. Maximum number of cell populations to try.

+#' Default \code{25}.

 #' @param tempL Integer. Number of temporary modules to identify and use in cell

 #'  splitting. Only used if \code{yInit = NULL}. Collapsing features to a

 #'  relatively smaller number of modules will increase the speed of clustering

 #'  and tend to produce better cell populations. This number should be larger

-#'  than the number of true modules expected in the dataset. Default NULL.

+#'  than the number of true modules expected in the dataset. Default

+#'  \code{NULL.}

 #' @param yInit Integer vector. Module labels for features. Cells will be

 #'  clustered using the \link{celda_CG} model based on the modules specified in

 #'  \code{yInit} rather than the counts of individual features. While the

 #'  features will be initialized to the module labels in \code{yInit}, the

 #'  labels will be allowed to move within each new model with a different K.

 #' @param alpha Numeric. Concentration parameter for Theta. Adds a pseudocount

-#'  to each cell population in each sample. Default 1.

+#'  to each cell population in each sample. Default \code{1}.

 #' @param beta Numeric. Concentration parameter for Phi. Adds a pseudocount to

 #'  each feature in each cell (if \code{yInit} is NULL) or to each module in

-#'  each cell population (if \code{yInit} is set). Default 1.

+#'  each cell population (if \code{yInit} is set). Default \code{1}.

 #' @param delta Numeric. Concentration parameter for Psi. Adds a pseudocount

 #'  to each feature in each module. Only used if \code{yInit} is set. Default 1.

 #' @param gamma Numeric. Concentration parameter for Eta. Adds a pseudocount

@@ -864,23 +867,23 @@ setMethod("recursiveSplitCell",

 #'  \link[SingleCellExperiment]{SingleCellExperiment} object. Default "counts".

 #' @param altExpName The name for the \link{altExp} slot

 #'  to use. Default "featureSubset".

-#' @param initialL Integer. Minimum number of modules to try.

-#' @param maxL Integer. Maximum number of modules to try.

+#' @param initialL Integer. Initial number of modules.

+#' @param maxL Integer. Maximum number of modules.

 #' @param tempK Integer. Number of temporary cell populations to identify and

 #'  use in module splitting. Only used if \code{zInit = NULL} Collapsing cells

 #'  to a relatively smaller number of cell popluations will increase the

 #'  speed of module clustering and tend to produce better modules. This number

 #'  should be larger than the number of true cell populations expected in the

-#'  dataset. Default 100.

+#'  dataset. Default \code{100}.

 #' @param zInit Integer vector. Collapse cells to cell populations based on

 #'  labels in \code{zInit} and then perform module splitting. If NULL, no

-#'  collapasing will be performed unless \code{tempK} is specified.

-#'  Default NULL.

+#'  collapsing will be performed unless \code{tempK} is specified.

+#'  Default \code{NULL}.

 #' @param sampleLabel Vector or factor. Denotes the sample label for each cell

-#'  (column) in the count matrix. Only used if \code{zInit} is set.

+#'  (column) in the count matrix. Default \code{NULL}.

 #' @param alpha Numeric. Concentration parameter for Theta. Adds a pseudocount

 #'  to each cell population in each sample. Only used if \code{zInit} is set.

-#'  Default 1.

+#'  Default \code{1}.

 #' @param beta Numeric. Concentration parameter for Phi. Adds a pseudocount

 #'  to each feature module in each cell. Default 1.

 #' @param delta Numeric. Concentration parameter for Psi. Adds a pseudocount

@@ -90,9 +90,9 @@

 #'  with the matrix located in the assay slot under \code{useAssay}.

 #'  Rows represent features and columns represent cells.

 #' @param useAssay A string specifying the name of the

-#'  \link[SummarizedExperiment]{assay}

+#'  \link{assay}

 #'  slot to use. Default "counts".

-#' @param altExpName The name for the \link[SingleCellExperiment]{altExp} slot

+#' @param altExpName The name for the \link{altExp} slot

 #'  to use. Default "featureSubset".

 #' @param sampleLabel Vector or factor. Denotes the sample label for each cell

 #'  (column) in the count matrix.

@@ -137,7 +137,7 @@

 #' @param ... Ignored. Placeholder to prevent check warning.

 #' @return A \linkS4class{SingleCellExperiment} object. Function

 #'  parameter settings and celda model results are stored in the

-#'  \link[S4Vectors]{metadata} \code{"celda_grid_search"} slot. The models in

+#'  \link{metadata} \code{"celda_grid_search"} slot. The models in

 #'  the list will be of class \code{celda_C} if \code{yInit = NULL} or