Merge branch 'scDD-est'

* scDD-est:
  Change mean-dropout to mean-zeros
  Add verbose to scDDEstimate

DESCRIPTION

 Package: splatter
 Type: Package
 Title: Simple Simulation of Single-cell RNA Sequencing Data
-Version: 1.1.2
-Date: 2017-07-16
+Version: 1.1.3
+Date: 2017-07-20
 Author: Luke Zappia
 Authors@R:
     c(person("Luke", "Zappia", role = c("aut", "cre"),

NEWS.md

+# 1.1.3
+
+* Add verbose option to scDDEstimate
+* Change "mean-dropout" to "mean-zeros" in compareSCESets
+
 # 1.1.2
 
 * Update summariseDiff

R/compare.R

@@ -29,7 +29,7 @@
 #'             \item{\code{ZerosCell}}{Boxplot of the percentage of each cell
 #'             that is zero.}
 #'             \item{\code{MeanZeros}}{Scatter plot with fitted lines showing
-#'             the mean-dropout relationship.}
+#'             the mean-zeros relationship.}
 #'     }
 #'   }
 #' }
@@ -164,7 +164,7 @@ compareSCESets <- function(sces, point.size = 0.1, point.alpha = 0.1,
         scale_fill_manual(values = colours) +
         xlab("Mean count") +
         ylab("Percentage zeros") +
-        ggtitle("Mean-dropout relationship") +
+        ggtitle("Mean-zeros relationship") +
         theme_minimal()
 
     if (fits) {

R/scDD-estimate.R

@@ -7,6 +7,7 @@
 #' @param conditions Vector giving the condition that each cell belongs to.
 #'        Conditions can be 1 or 2.
 #' @param params SCDDParams object to store estimated values in.
+#' @param verbose logical. Whether to show progress messages.
 #' @param BPPARAM A \code{\link[BiocParallel]{BiocParallelParam}} instance
 #'        giving the parallel back-end to be used. Default is
 #'        \code{\link[BiocParallel]{SerialParam}} which uses a single core.
@@ -29,23 +30,23 @@
 #' @importFrom BiocParallel SerialParam
 #' @export
 scDDEstimate <- function(counts, conditions, params = newSCDDParams(),
-                         BPPARAM = SerialParam()) {
+                         verbose = TRUE, BPPARAM = SerialParam()) {
     UseMethod("scDDEstimate")
 }
 
 #' @rdname scDDEstimate
 #' @export
 scDDEstimate.SCESet <- function(counts, conditions, params = newSCDDParams(),
-                                BPPARAM = SerialParam()) {
+                                verbose = TRUE, BPPARAM = SerialParam()) {
     counts <- scater::counts(counts)
-    scDDEstimate(counts, conditions, params)
+    scDDEstimate(counts, conditions, params, verbose, BPPARAM)
 }
 
 #' @rdname scDDEstimate
 #' @importFrom methods as
 #' @export
 scDDEstimate.matrix <- function(counts, conditions, params = newSCDDParams(),
-                                BPPARAM = SerialParam()) {
+                                verbose = TRUE, BPPARAM = SerialParam()) {
 
     if (!requireNamespace("scDD", quietly = TRUE)) {
         stop("The scDD simulation requires the 'scDD' package.")
@@ -61,8 +62,15 @@ scDDEstimate.matrix <- function(counts, conditions, params = newSCDDParams(),
     counts.list <- list(Cond1 = counts[, conditions == 1],
                         Cond2 = counts[, conditions == 2])
 
-    processed <- scDD::preprocess(counts.list, c("Cond1", "Cond2"),
-                                  median_norm = TRUE)
+    if (verbose) {
+        processed <- scDD::preprocess(counts.list, c("Cond1", "Cond2"),
+                                      median_norm = TRUE)
+    } else {
+        suppressMessages(
+        processed <- scDD::preprocess(counts.list, c("Cond1", "Cond2"),
+                                      median_norm = TRUE)
+        )
+    }
 
     assays <- S4Vectors::SimpleList(NormCounts = processed)
 
@@ -72,7 +80,13 @@ scDDEstimate.matrix <- function(counts, conditions, params = newSCDDParams(),
     SCdat <- SummarizedExperiment::SummarizedExperiment(assays = assays,
                                                         colData = colData)
 
-    SCdat <- scDD::scDD(SCdat, testZeroes = FALSE, param = BPPARAM)
+    if (verbose) {
+        SCdat <- scDD::scDD(SCdat, testZeroes = FALSE, param = BPPARAM)
+    } else {
+        dummy <- utils::capture.output(suppressMessages(
+        SCdat <- scDD::scDD(SCdat, testZeroes = FALSE, param = BPPARAM)
+        ))
+    }
 
     res <- scDD::results(SCdat)
     res <- res[!is.na(res$DDcategory), ]

man/compareSCESets.Rd

@@ -45,7 +45,7 @@ The returned list has three items:
             \item{\code{ZerosCell}}{Boxplot of the percentage of each cell
             that is zero.}
             \item{\code{MeanZeros}}{Scatter plot with fitted lines showing
-            the mean-dropout relationship.}
+            the mean-zeros relationship.}
     }
   }
 }

man/scDDEstimate.Rd

@@ -6,14 +6,14 @@
 \alias{scDDEstimate.matrix}
 \title{Estimate scDD simulation parameters}
 \usage{
-scDDEstimate(counts, conditions, params = newSCDDParams(),
+scDDEstimate(counts, conditions, params = newSCDDParams(), verbose = TRUE,
   BPPARAM = SerialParam())
 
 \method{scDDEstimate}{SCESet}(counts, conditions, params = newSCDDParams(),
-  BPPARAM = SerialParam())
+  verbose = TRUE, BPPARAM = SerialParam())
 
 \method{scDDEstimate}{matrix}(counts, conditions, params = newSCDDParams(),
-  BPPARAM = SerialParam())
+  verbose = TRUE, BPPARAM = SerialParam())
 }
 \arguments{
 \item{counts}{either a counts matrix or an SCESet object containing count
@@ -24,6 +24,8 @@ Conditions can be 1 or 2.}
 
 \item{params}{SCDDParams object to store estimated values in.}
 
+\item{verbose}{logical. Whether to show progress messages.}
+
 \item{BPPARAM}{A \code{\link[BiocParallel]{BiocParallelParam}} instance
 giving the parallel back-end to be used. Default is
 \code{\link[BiocParallel]{SerialParam}} which uses a single core.}