@@ -129,6 +129,7 @@ importFrom(scales,hue_pal)

 importFrom(stringi,stri_list2matrix)

 importFrom(umap,umap)

 importFrom(umap,umap.defaults)

+importFrom(withr,with_seed)

 useDynLib(celda,"_colSumByGroup")

 useDynLib(celda,"_colSumByGroupChange")

 useDynLib(celda,"_colSumByGroup_numeric")

@@ -601,9 +601,11 @@ setGeneric("celdaTsne",

 #'  for umap. Default 20.

 #' @param modules Integer vector. Determines which features modules to use for

 #'  tSNE. If NULL, all modules will be used. Default NULL.

+#' @param seed Integer. Passed to \link[withr]{with_seed}. For reproducibility,

+#'  a default value of 12345 is used. If NULL, no calls to

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

 #' @param umapConfig An object of class "umapConfig" specifying parameters to

 #'  the UMAP algorithm.

-#' @param ... Additional parameters.

 #' @return Numeric Matrix of dimension `ncol(counts)` x 2, colums representing

 #'  the "X" and "Y" coordinates in the data's t-SNE represetation.

 #' @examples

@@ -619,6 +621,7 @@ setGeneric("celdaUmap",

         minClusterSize = 100,

         initialDims = 20,

         modules = NULL,

+        seed = 12345,

         umapConfig = umap::umap.defaults) {

         standardGeneric("celdaUmap")

     })

@@ -795,7 +795,6 @@ setMethod("factorizeMatrix", signature(celdaMod = "celda_C"),

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

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

 #'  each feature in each cell population. Default 1.

-#' @param ... Additional parameters.

 #' @return Numeric. The log likelihood for the given cluster assignments

 #' @seealso `celda_C()` for clustering cells

 #' @examples

@@ -1141,7 +1140,6 @@ setMethod("celdaTsne", signature(celdaMod = "celda_C"),

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

 #' @param umapConfig An object of class "umap.config" specifying parameters to

 #'  the UMAP algorithm.

-#' @param ... Additional parameters.

 #' @seealso `celda_C()` for clustering cells and `celdaHeatmap()` for displaying

 #'  expression.

 #' @examples

@@ -986,7 +986,6 @@ setMethod("factorizeMatrix", signature(celdaMod = "celda_CG"),

 #'  each feature in each module. Default 1.

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

 #'  the number of features in each module. Default 1.

-#' @param ... Additional parameters.

 #' @return The log likelihood for the given cluster assignments

 #' @seealso `celda_CG()` for clustering features and cells

 #' @examples

@@ -758,7 +758,6 @@ setMethod("factorizeMatrix", signature(celdaMod = "celda_G"),

 #'  each feature in each module. Default 1.

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

 #'  the number of features in each module. Default 1.

-#' @param ... Additional parameters.

 #' @keywords log likelihood

 #' @return The log-likelihood for the given cluster assignments.

 #' @seealso `celda_G()` for clustering features

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

 \usage{

 \S4method{celdaTsne}{celda_C}(counts, celdaMod, maxCells = 25000,

   minClusterSize = 100, initialDims = 20, modules = NULL,

-  perplexity = 20, maxIter = 2500)

+  perplexity = 20, maxIter = 2500, seed = 12345)

 }

 \arguments{

 \item{counts}{Integer matrix. Rows represent features and columns represent

@@ -34,6 +34,10 @@ tSNE. If NULL, all modules will be used. Default NULL.}

 \item{maxIter}{Integer. Maximum number of iterations in tSNE generation.

 Default 2500.}

+

+\item{seed}{Integer. Passed to \link[withr]{with_seed}. For reproducibility,

+a default value of 12345 is used. If NULL, no calls to

+\link[withr]{with_seed} are made.}

 }

 \value{

 A two column matrix of t-SNE coordinates

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

 \usage{

 \S4method{celdaTsne}{celda_CG}(counts, celdaMod, maxCells = 25000,

   minClusterSize = 100, initialDims = 20, modules = NULL,

-  perplexity = 20, maxIter = 2500)

+  perplexity = 20, maxIter = 2500, seed = 12345)

 }

 \arguments{

 \item{counts}{Integer matrix. Rows represent features and columns represent

@@ -34,6 +34,10 @@ tSNE. If NULL, all modules will be used. Default NULL.}

 \item{maxIter}{Integer. Maximum number of iterations in tSNE generation.

 Default 2500.}

+

+\item{seed}{Integer. Passed to \link[withr]{with_seed}. For reproducibility,

+a default value of 12345 is used. If NULL, no calls to

+\link[withr]{with_seed} are made.}

 }

 \value{

 A two column matrix of t-SNE coordinates

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

 \usage{

 \S4method{celdaTsne}{celda_G}(counts, celdaMod, maxCells = 25000,

   minClusterSize = 100, initialDims = 20, modules = NULL,

-  perplexity = 20, maxIter = 2500)

+  perplexity = 20, maxIter = 2500, seed = 12345)

 }

 \arguments{

 \item{counts}{Integer matrix. Rows represent features and columns represent

@@ -34,6 +34,10 @@ tSNE. If NULL, all modules will be used. Default NULL.}

 \item{maxIter}{Integer. Maximum number of iterations in tSNE generation.

 Default 2500.}

+

+\item{seed}{Integer. Passed to \link[withr]{with_seed}. For reproducibility,

+a default value of 12345 is used. If NULL, no calls to

+\link[withr]{with_seed} are made.}

 }

 \value{

 A two column matrix of t-SNE coordinates.

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

 \title{umap for celda_C}

 \usage{

 \S4method{celdaUmap}{celda_C}(counts, celdaMod, maxCells = 25000,

-  minClusterSize = 100, modules = NULL,

+  minClusterSize = 100, modules = NULL, seed = 12345,

   umapConfig = umap::umap.defaults)

 }

 \arguments{

@@ -26,10 +26,12 @@ threshold. Default 100.}

 \item{modules}{Integer vector. Determines which features modules to use for

 UMAP. If NULL, all modules will be used. Default NULL.}

+\item{seed}{Integer. Passed to \link[withr]{with_seed}. For reproducibility,

+a default value of 12345 is used. If NULL, no calls to

+\link[withr]{with_seed} are made.}

+

 \item{umapConfig}{An object of class "umap.config" specifying parameters to

 the UMAP algorithm.}

-

-\item{...}{Additional parameters.}

 }

 \value{

 A two column matrix of umap coordinates

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

 \title{umap for celda_CG}

 \usage{

 \S4method{celdaUmap}{celda_CG}(counts, celdaMod, maxCells = 25000,

-  minClusterSize = 100, modules = NULL,

+  minClusterSize = 100, modules = NULL, seed = 12345,

   umapConfig = umap::umap.defaults)

 }

 \arguments{

@@ -26,6 +26,10 @@ threshold. Default 100.}

 \item{modules}{Integer vector. Determines which features modules to use for

 tSNE. If NULL, all modules will be used. Default NULL.}

+\item{seed}{Integer. Passed to \link[withr]{with_seed}. For reproducibility,

+a default value of 12345 is used. If NULL, no calls to

+\link[withr]{with_seed} are made.}

+

 \item{umapConfig}{Object of class `umap.config`. Configures parameters for

 umap. Default `umap::umap.defaults`.}

 }

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

 \title{umap for celda_G}

 \usage{

 \S4method{celdaUmap}{celda_G}(counts, celdaMod, maxCells = 25000,

-  minClusterSize = 100, modules = NULL,

+  minClusterSize = 100, modules = NULL, seed = 12345,

   umapConfig = umap::umap.defaults)

 }

 \arguments{

@@ -26,6 +26,10 @@ threshold. Default 100.}

 \item{modules}{Integer vector. Determines which features modules to use for

 tSNE. If NULL, all modules will be used. Default NULL.}

+\item{seed}{Integer. Passed to \link[withr]{with_seed}. For reproducibility,

+a default value of 12345 is used. If NULL, no calls to

+\link[withr]{with_seed} are made.}

+

 \item{umapConfig}{Object of class `umap.config`. Configures parameters for

 umap. Default `umap::umap.defaults`.}

 }

@@ -5,7 +5,8 @@

 \title{Embeds cells in two dimensions using umap.}

 \usage{

 celdaUmap(counts, celdaMod, maxCells = 25000, minClusterSize = 100,

-  initialDims = 20, modules = NULL, umapConfig = umap::umap.defaults)

+  initialDims = 20, modules = NULL, seed = 12345,

+  umapConfig = umap::umap.defaults)

 }

 \arguments{

 \item{counts}{Integer matrix. Rows represent features and columns represent

@@ -28,10 +29,12 @@ for umap. Default 20.}

 \item{modules}{Integer vector. Determines which features modules to use for

 tSNE. If NULL, all modules will be used. Default NULL.}

+\item{seed}{Integer. Passed to \link[withr]{with_seed}. For reproducibility,

+a default value of 12345 is used. If NULL, no calls to

+\link[withr]{with_seed} are made.}

+

 \item{umapConfig}{An object of class "umapConfig" specifying parameters to

 the UMAP algorithm.}

-

-\item{...}{Additional parameters.}

 }

 \value{

 Numeric Matrix of dimension `ncol(counts)` x 2, colums representing

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

 \usage{

 celda_C(counts, sampleLabel = NULL, K, alpha = 1, beta = 1,

   algorithm = c("EM", "Gibbs"), stopIter = 10, maxIter = 200,

-  splitOnIter = 10, splitOnLast = TRUE, nchains = 3,

+  splitOnIter = 10, splitOnLast = TRUE, seed = 12345, nchains = 3,

   zInitialize = c("split", "random", "predefined"),

   countChecksum = NULL, zInit = NULL, logfile = NULL,

   verbose = TRUE)

@@ -49,6 +49,10 @@ a cell population should be reassigned and another cell population should be

 split into two clusters. If a split occurs, then `stopIter` will be reset.

 Default TRUE.}

+\item{seed}{Integer. Passed to \link[withr]{with_seed}. For reproducibility,

+a default value of 12345 is used. If NULL, no calls to

+\link[withr]{with_seed} are made.}

+

 \item{nchains}{Integer. Number of random cluster initializations. Default 3.}

 \item{zInitialize}{Chararacter. One of 'random', 'split', or 'predefined'.

@@ -7,8 +7,9 @@

 celda_CG(counts, sampleLabel = NULL, K, L, alpha = 1, beta = 1,

   delta = 1, gamma = 1, algorithm = c("EM", "Gibbs"),

   stopIter = 10, maxIter = 200, splitOnIter = 10,

-  splitOnLast = TRUE, nchains = 3, zInitialize = c("split", "random",

-  "predefined"), yInitialize = c("split", "random", "predefined"),

+  splitOnLast = TRUE, seed = 12345, nchains = 3,

+  zInitialize = c("split", "random", "predefined"),

+  yInitialize = c("split", "random", "predefined"),

   countChecksum = NULL, zInit = NULL, yInit = NULL, logfile = NULL,

   verbose = TRUE)

 }

@@ -57,6 +58,10 @@ a cell population or feature module should be reassigned and another cell

 population or feature module should be split into two clusters. If a split

 occurs, then 'stopIter' will be reset. Default TRUE.}

+\item{seed}{Integer. Passed to \link[withr]{with_seed}. For reproducibility,

+a default value of 12345 is used. If NULL, no calls to

+\link[withr]{with_seed} are made.}

+

 \item{nchains}{Integer. Number of random cluster initializations. Default 3.}

 \item{zInitialize}{Chararacter. One of 'random', 'split', or 'predefined'.

@@ -5,9 +5,9 @@

 \title{Feature clustering with Celda}

 \usage{

 celda_G(counts, L, beta = 1, delta = 1, gamma = 1, stopIter = 10,

-  maxIter = 200, splitOnIter = 10, splitOnLast = TRUE, nchains = 3,

-  yInitialize = c("split", "random", "predefined"),

-  countChecksum = NULL, yInit = NULL, logfile = NULL,

+  maxIter = 200, splitOnIter = 10, splitOnLast = TRUE,

+  seed = 12345, nchains = 3, yInitialize = c("split", "random",

+  "predefined"), countChecksum = NULL, yInit = NULL, logfile = NULL,

   verbose = TRUE)

 }

 \arguments{

@@ -42,6 +42,10 @@ a cell population should be reassigned and another cell population should be

 split into two clusters. If a split occurs, then `stopIter` will be reset.

 Default TRUE.}

+\item{seed}{Integer. Passed to \link[withr]{with_seed}. For reproducibility,

+a default value of 12345 is used. If NULL, no calls to

+\link[withr]{with_seed} are made.}

+

 \item{nchains}{Integer. Number of random cluster initializations. Default 3.}

 \item{yInitialize}{Chararacter. One of 'random', 'split', or 'predefined'.

@@ -5,7 +5,8 @@

 \title{Decontaminate count matrix}

 \usage{

 decontX(counts, z = NULL, batch = NULL, maxIter = 200,

-  beta = 1e-06, delta = 10, logfile = NULL, verbose = TRUE)

+  beta = 1e-06, delta = 10, logfile = NULL, verbose = TRUE,

+  seed = 12345)

 }

 \arguments{

 \item{counts}{Numeric/Integer matrix. Observed count matrix, rows represent

@@ -27,6 +28,10 @@ to be 10.}

 `logfile`. If NULL, messages will be printed to stdout.  Default NULL.}

 \item{verbose}{Logical. Whether to print log messages. Default TRUE.}

+

+\item{seed}{Integer. Passed to \link[withr]{with_seed}. For reproducibility,

+a default value of 12345 is used. If NULL, no calls to

+\link[withr]{with_seed} are made.}

 }

 \value{

 A list object which contains the decontaminated count matrix and

@@ -22,8 +22,6 @@ to each cell population in each sample. Default 1.}

 \item{beta}{Numeric. Concentration parameter for Phi. Adds a pseudocount to

 each feature in each cell population. Default 1.}

-

-\item{...}{Additional parameters.}

 }

 \value{

 Numeric. The log likelihood for the given cluster assignments

@@ -33,8 +33,6 @@ each feature in each module. Default 1.}

 \item{gamma}{Numeric. Concentration parameter for Eta. Adds a pseudocount to

 the number of features in each module. Default 1.}

-

-\item{...}{Additional parameters.}

 }

 \value{

 The log likelihood for the given cluster assignments

@@ -22,8 +22,6 @@ each feature in each module. Default 1.}

 \item{gamma}{Numeric. Concentration parameter for Eta. Adds a pseudocount to

 the number of features in each module. Default 1.}

-

-\item{...}{Additional parameters.}

 }

 \value{

 The log-likelihood for the given cluster assignments.

@@ -29,8 +29,8 @@ in the featureModule. If NULL, plot all features in the module. Default

 NULL.}

 \item{normalizedCounts}{Integer matrix. Rows represent features and columns

-represent cells. This matrix should correspond to the one provided for 

-`counts`, but should be passed through. If NA, normalize `counts`. 

+represent cells. This matrix should correspond to the one provided for

+`counts`, but should be passed through. If NA, normalize `counts`.

 Default NA.

 `normalizeCounts(counts, "proportion", transformationFun=sqrt)`. Use of this

 parameter is particularly useful for plotting many moduleHeatmaps, where

@@ -5,7 +5,7 @@

 \title{Calculate and visualize perplexity of all models in a celdaList, with

  count resampling}

 \usage{

-resamplePerplexity(counts, celdaList, resample = 5)

+resamplePerplexity(counts, celdaList, resample = 5, seed = 12345)

 }

 \arguments{

 \item{counts}{Integer matrix. Rows represent features and columns represent

@@ -16,6 +16,10 @@ cells. This matrix should be the same as the one used to generate

 \item{resample}{Integer. The number of times to resample the counts matrix

 for evaluating perplexity. Default 5.}

+

+\item{seed}{Integer. Passed to \link[withr]{with_seed}. For reproducibility,

+a default value of 12345 is used. If NULL, no calls to

+\link[withr]{with_seed} are made.}

 }

 \value{

 celdaList. Returns the provided `celdaList` with a `perplexity`

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

 \usage{

 simulateCellscelda_C(model, S = 5, CRange = c(50, 100),

   NRange = c(500, 1000), G = 100, K = 5, alpha = 1, beta = 1,

-  ...)

+  seed = 12345, ...)

 }

 \arguments{

 \item{model}{Character. Options available in `celda::availableModels`.}

@@ -31,6 +31,10 @@ to each cell population in each sample. Default 1.}

 \item{beta}{Numeric. Concentration parameter for Phi. Adds a pseudocount to

 each feature in each cell population. Default 1.}

+\item{seed}{Integer. Passed to \link[withr]{with_seed}. For reproducibility,

+a default value of 12345 is used. If NULL, no calls to

+\link[withr]{with_seed} are made.}

+

 \item{...}{Additional parameters.}

 }

 \value{

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

 \usage{

 simulateCellscelda_CG(model, S = 5, CRange = c(50, 100),

   NRange = c(500, 1000), G = 100, K = 5, L = 10, alpha = 1,

-  beta = 1, gamma = 5, delta = 1, ...)

+  beta = 1, gamma = 5, delta = 1, seed = 12345, ...)

 }

 \arguments{

 \item{model}{Character. Options available in `celda::availableModels`.}

@@ -39,6 +39,10 @@ the number of features in each module. Default 5.}

 \item{delta}{Numeric. Concentration parameter for Psi. Adds a pseudocount to

 each feature in each module. Default 1.}

+\item{seed}{Integer. Passed to \link[withr]{with_seed}. For reproducibility,

+a default value of 12345 is used. If NULL, no calls to

+\link[withr]{with_seed} are made.}

+

 \item{...}{Additional parameters.}

 }

 \value{

@@ -5,7 +5,7 @@

 \title{Simulate cells from the celda_G model}

 \usage{

 simulateCellscelda_G(model, C = 100, NRange = c(500, 1000), G = 100,

-  L = 10, beta = 1, gamma = 5, delta = 1, ...)

+  L = 10, beta = 1, gamma = 5, delta = 1, seed = 12345, ...)

 }

 \arguments{

 \item{model}{Character. Options available in `celda::availableModels`.}

@@ -29,6 +29,10 @@ the number of features in each module. Default 5.}

 \item{delta}{Numeric. Concentration parameter for Psi. Adds a pseudocount to

 each feature in each module. Default 1.}

+\item{seed}{Integer. Passed to \link[withr]{with_seed}. For reproducibility,

+a default value of 12345 is used. If NULL, no calls to

+\link[withr]{with_seed} are made.}

+

 \item{...}{Additional parameters.}

 }

 \value{

@@ -5,7 +5,7 @@

 \title{Simulate contaminated count matrix}

 \usage{

 simulateContaminatedMatrix(C = 300, G = 100, K = 3, NRange = c(500,

-  1000), beta = 0.5, delta = c(1, 2))

+  1000), beta = 0.5, delta = c(1, 2), seed = 12345)

 }

 \arguments{

 \item{C}{Integer. Number of cells to be simulated. Default to be 300.}

@@ -25,6 +25,10 @@ be c(500, 1000).}

 input as a single numeric value, symmetric values for beta distribution are

 specified; if input as a vector of lenght 2, the two values will be the

 shape1 and shape2 paramters of the beta distribution respectively.}

+

+\item{seed}{Integer. Passed to \link[withr]{with_seed}. For reproducibility,

+a default value of 12345 is used. If NULL, no calls to

+\link[withr]{with_seed} are made.}

 }

 \value{

 A list object containing the real expression matrix and contamination