Merge 116a9fe into ac07278

compbiomed · Oct 8, 2023 · 2f9d9db · 2f9d9db
2 parents ac07278 + 116a9fe
commit 2f9d9db
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Showing 12 changed files with 47 additions and 29 deletions.
diff --git a/R/doubletFinder_doubletDetection.R b/R/doubletFinder_doubletDetection.R
@@ -397,7 +397,7 @@ runDoubletFinder <- function(inSCE,
       if (length(seuratPcs) > ncol(mat)) {
         seuratPcs <- seq(ncol(mat))
       }
-      .withSeed(seed, {
+      withr::with_seed(seed, {
         result <- .runDoubletFinder(
           counts = mat,
           seuratPcs = seuratPcs,

diff --git a/R/miscFunctions.R b/R/miscFunctions.R
@@ -464,6 +464,9 @@ getGenesetNamesFromCollection <- function(inSCE, geneSetCollectionName) {
   return(names(geneSet))
 }
 
+# deprecating
+# does not work as intended
+# instead directly using withr::with_seed
 .withSeed <- function(seed, code) {
   if (is.null(seed)) {
     code

diff --git a/R/runBatchCorrection.R b/R/runBatchCorrection.R
@@ -296,6 +296,7 @@ runFastMNN <- function(inSCE, useAssay = "logcounts", useReducedDim = NULL,
 #' make soft kmeans cluster approach hard clustering. Default \code{0.1}.
 #' @param nIter An integer. The max number of iterations to perform. Default
 #' \code{10L}.
+#' @param seed Set seed for reproducibility. Default is \code{12345}.
 #' @param verbose Whether to print progress messages. Default \code{TRUE}.
 #' @param ... Other arguments passed to \code{\link[harmony]{HarmonyMatrix}}.
 #' See details.
@@ -318,7 +319,7 @@ runFastMNN <- function(inSCE, useAssay = "logcounts", useReducedDim = NULL,
 runHarmony <- function(inSCE, useAssay = "logcounts", useReducedDim = NULL,
                        batch = "batch", reducedDimName = "HARMONY",
                        nComponents = 50, lambda = 0.1, theta = 5,
-                       sigma = 0.1, nIter = 10, verbose = TRUE, ...) {
+                       sigma = 0.1, nIter = 10, seed = 12345, verbose = TRUE, ...) {
   if (!requireNamespace("harmony", quietly = TRUE)) {
     stop("The Harmony package is required to run this function. ",
          "Install harmony with: ",
@@ -342,11 +343,13 @@ runHarmony <- function(inSCE, useAssay = "logcounts", useReducedDim = NULL,
     }
     mat <- mat[,seq(nComponents)]
   }
-  h <- harmony::HarmonyMatrix(data_mat = mat, meta_data = batchVec,
-                              do_pca = do_pca, npcs = nComponents,
-                              lambda = lambda, theta = theta,
-                              sigma = sigma, max.iter.harmony = nIter,
-                              verbose = verbose, return_object = FALSE, ...)
+  h <- withr::with_seed(seed, {
+    harmony::HarmonyMatrix(data_mat = mat, meta_data = batchVec,
+                           do_pca = do_pca, npcs = nComponents,
+                           lambda = lambda, theta = theta,
+                           sigma = sigma, max.iter.harmony = nIter,
+                           verbose = verbose, return_object = FALSE, ...)
+  })
   SingleCellExperiment::reducedDim(inSCE, reducedDimName) <- h
   S4Vectors::metadata(inSCE)$batchCorr[[reducedDimName]] <-
     list(useAssay = useAssay, origLogged = TRUE, method = "harmony",

diff --git a/R/runCluster.R b/R/runCluster.R
@@ -235,7 +235,7 @@ runKMeans <- function(inSCE, nCenters, useReducedDim = "PCA",
     if (nComp < ncol(mat)) {
         mat <- mat[,seq(nComp)]
     }
-    .withSeed(seed, {
+    withr::with_seed(seed, {
         clust.kmeans <- stats::kmeans(mat, centers = nCenters, iter.max = nIter,
                                   nstart = nStart, algorithm = algorithm)
     })

diff --git a/R/runTSNE.R b/R/runTSNE.R
@@ -134,7 +134,7 @@ runTSNE <- function(inSCE, useReducedDim = "PCA", useAssay = NULL,
   # Rtsne requires a matrix input
   mat <- as.matrix(mat)
   message(paste0(date(), " ... Computing Rtsne."))
-  .withSeed(seed, {
+  withr::with_seed(seed, {
     tsneOut <- Rtsne::Rtsne(mat, pca_scale = scale, pca_center = center,
                             pca = pca, partial_pca = partialPCA,
                             perplexity = perplexity,

diff --git a/R/runUMAP.R b/R/runUMAP.R
@@ -127,8 +127,8 @@ runUMAP <- function(inSCE, useReducedDim = "PCA", useAssay = NULL,
                    samples[i], "'."))
     }
 
-    .withSeed(seed, {
-      umapRes <- scater::calculateUMAP(sceSample, exprs_values = useAssayTemp,
+    umapRes <- withr::with_seed(seed, {
+      scater::calculateUMAP(sceSample, exprs_values = useAssayTemp,
                                        dimred = useReducedDim, scale = scale,
                                        n_neighbors = nNeighbors,
                                        learning_rate = alpha,

diff --git a/R/scDblFinder_doubletDetection.R b/R/scDblFinder_doubletDetection.R
@@ -66,7 +66,7 @@ runScDblFinder <- function(inSCE,
     inSCE <- inSCE[,-rm.ix]
     sample <- sample[-rm.ix]
   }
-  .withSeed(seed, {
+  withr::with_seed(seed, {
     inSCE <- scDblFinder::scDblFinder(sce = inSCE,
                                       samples = sample,
                                       artificialDoublets = simDoublets,

diff --git a/R/scater_PCA.R b/R/scater_PCA.R
@@ -57,7 +57,7 @@ scaterPCA <- function(inSCE, useAssay = "logcounts", useFeatureSubset = NULL,
   subset_row <- .parseUseFeatureSubset(inSCE, useFeatureSubset,
                                        altExpObj = sce, returnType = "logical")
   message(paste0(date(), " ... Computing Scater PCA."))
-  .withSeed(seed, {
+  withr::with_seed(seed, {
     pca <- scater::calculatePCA(useMat$mat, ncomponents = nComponents,
                                 scale = scale, ntop = ntop,
                                 subset_row = subset_row, BPPARAM = BPPARAM)

diff --git a/R/scds_doubletdetection.R b/R/scds_doubletdetection.R
@@ -78,7 +78,7 @@ runCxds <- function(
     nGene <- ntop
     while (!inherits(result, "SingleCellExperiment") & nGene > 0) {
       try({
-        result <- .withSeed(seed, {
+        result <- withr::with_seed(seed, {
           scds::cxds(sce = sceSample,
                      ntop = nGene,
                      binThresh = binThresh,
@@ -210,7 +210,7 @@ runBcds <- function(
     nGene <- ntop
     while (!inherits(result, "SingleCellExperiment") & nGene > 0) {
       try({
-        result <- .withSeed(seed, {
+        result <- withr::with_seed(seed, {
           scds::bcds(sce = sceSample,
                      ntop = nGene,
                      srat = srat,
@@ -349,7 +349,7 @@ runCxdsBcdsHybrid <- function(inSCE,
     nGene <- min(nGene.cxds, nGene.bcds)
     while (!inherits(result, "SingleCellExperiment") & nGene > 0) {
       try({
-        result <- .withSeed(seed, {
+        result <- withr::with_seed(seed, {
           scds::cxds_bcds_hybrid(sce = sceSample,
                                  cxdsArgs = c(list(ntop = nGene.cxds), 
                                               cxdsArgs),

diff --git a/R/seuratFunctions.R b/R/seuratFunctions.R
@@ -733,6 +733,7 @@ plotSeuratReduction <-
 #' not. Default \code{TRUE}.
 #' @param resolution Set the resolution parameter to find larger (value above 1)
 #' or smaller (value below 1) number of communities. Default \code{0.8}.
+#' @param seed Specify the seed value. Default \code{12345}.
 #' @param externalReduction Pass DimReduc object if PCA/ICA computed through
 #' other libraries. Default \code{NULL}.
 #' @param verbose Logical value indicating if informative messages should
@@ -755,6 +756,7 @@ runSeuratFindClusters <- function(inSCE,
                                   algorithm = c("louvain", "multilevel", "SLM"),
                                   groupSingletons = TRUE,
                                   resolution = 0.8,
+                                  seed = 12345,
                                   externalReduction = NULL,
                                   verbose = TRUE) {
   algorithm <- match.arg(algorithm)
@@ -773,12 +775,14 @@ runSeuratFindClusters <- function(inSCE,
     }
   }
 
-  seuratObject <- Seurat::FindNeighbors(
-    seuratObject,
-    reduction = useReduction,
-    dims = seq(dims),
-    verbose = verbose
-  )
+  seuratObject <- withr::with_seed(seed, {
+    Seurat::FindNeighbors(
+      seuratObject,
+      reduction = useReduction,
+      dims = seq(dims),
+      verbose = verbose
+    )
+  })
 
   no_algorithm <- 1
   if (algorithm == "louvain") {
@@ -790,13 +794,15 @@ runSeuratFindClusters <- function(inSCE,
   }
   tempSeuratObject <- seuratObject
   tempSeuratObject@meta.data <- data.frame()
-  tempSeuratObject <- Seurat::FindClusters(
-    tempSeuratObject,
-    algorithm = no_algorithm,
-    group.singletons = groupSingletons,
-    resolution = resolution,
-    verbose = verbose
-  )
+  tempSeuratObject <- withr::with_seed(seed, {
+    Seurat::FindClusters(
+      tempSeuratObject,
+      algorithm = no_algorithm,
+      group.singletons = groupSingletons,
+      resolution = resolution,
+      verbose = verbose
+    )
+  })
   seuratObject@meta.data$seurat_clusters <-
     tempSeuratObject@meta.data$seurat_clusters
   inSCE <- .addSeuratToMetaDataSCE(inSCE, seuratObject)

diff --git a/man/runHarmony.Rd b/man/runHarmony.Rd
diff --git a/man/runSeuratFindClusters.Rd b/man/runSeuratFindClusters.Rd