Devel

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: celda
 Title: CEllular Latent Dirichlet Allocation
-Version: 0.99.39
+Version: 1.1.1
 Authors@R: c(person("Joshua", "Campbell", email = "camp@bu.edu", role = c("aut", "cre")),
              person("Sean", "Corbett", email = "scorbett@bu.edu", role = c("aut")),
 	     person("Yusuke", "Koga", email="ykoga07@bu.edu", role = c("aut")),
@@ -38,7 +38,8 @@ Imports:
     SummarizedExperiment,
     MCMCprecision,
     ggrepel,
-    Rtsne
+    Rtsne,
+    withr
 Suggests:
     testthat,
     knitr,

NAMESPACE

@@ -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")

R/StateHeatmap.R

@@ -19,8 +19,13 @@
 #' @param topFeatures Integer. Plot `topFeatures` with the highest probability
 #'  in the featureModule. If NULL, plot all features in the module. Default
 #'  NULL.
-#' @param normalize Logical. Whether to normalize the columns of `counts`.
-#'  Default TRUE.
+#' @param 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`.
+#'  Default NA.
+#'  `normalizeCounts(counts, "proportion", transformationFun=sqrt)`. Use of this
+#'  parameter is particularly useful for plotting many moduleHeatmaps, where
+#'  normalizing the counts matrix repeatedly would be too time consuming.
 #' @param scaleRow Character. Which function to use to scale each individual
 #'  row. Set to NULL to disable. Occurs after normalization and log
 #'  transformation. For example, `scale` will Z-score transform each row.
@@ -39,7 +44,7 @@ moduleHeatmap <- function(counts,
     featureModule = 1,
     topCells = 100,
     topFeatures = NULL,
-    normalize = TRUE,
+    normalizedCounts = NA,
     scaleRow = scale,
     showFeaturenames = TRUE) {
 
@@ -93,11 +98,11 @@ moduleHeatmap <- function(counts,
     }
 
     cellIndices <- rev(cellIndices)
-    if (normalize) {
+    if (is.na(normalizedCounts)) {
       normCounts <- normalizeCounts(counts, normalize = "proportion",
           transformationFun = sqrt)
     } else {
-        normCounts <- counts
+        normCounts <- normalizedCounts
     }
 
     # filter counts based on featureIndices

R/all_generics.R

@@ -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")
     })