change generic subset.FRASER drop, and formal argument matching in se…

…tMethod

DESCRIPTION

@@ -28,7 +28,7 @@ biocViews:
 License: MIT + file LICENSE
 URL: https://github.com/gagneurlab/FRASER
 BugRepots: https://github.com/gagneurlab/FRASER/issues
-RoxygenNote: 7.3.0
+RoxygenNote: 7.3.1
 Encoding: UTF-8
 VignetteBuilder: knitr
 Depends:

R/AllGenerics.R

@@ -236,12 +236,12 @@ setReplaceMethod("nonSplicedReads", "FraserDataSet", function(object, value){
 #' @return A subsetted \code{FraserDataSet} object
 #' @examples
 #'     fds <- createTestFraserDataSet()
-#'     fds[1:10,2:3,,drop=FALSE]
-#'     fds[,samples(fds) %in% c("sample1", "sample2"),,drop=FALSE]
-#'     fds[1:10,by="ss",,drop=FALSE]
+#'     fds[1:10,2:3]
+#'     fds[,samples(fds) %in% c("sample1", "sample2")]
+#'     fds[1:10,by="ss"]
 #'
 #' @rdname subset
-subset.FRASER <- function(x, i, j, by=c("j", "ss"), drop = FALSE){
+subset.FRASER <- function(x, i, j, by=c("j", "ss"), ..., drop=FALSE){
     if(length(by) == 1){
         by <- whichReadType(x, by)
     }
@@ -312,7 +312,7 @@ subset.FRASER <- function(x, i, j, by=c("j", "ss"), drop = FALSE){
 }
 #' @rdname subset
 #' @export
-setMethod("[", c("FraserDataSet", "ANY", "ANY"), subset.FRASER)
+setMethod("[", c("FraserDataSet", "ANY", "ANY", drop="ANY"), subset.FRASER)
 
 
 #'
@@ -673,7 +673,7 @@ FRASER.results <- function(object, sampleIDs, fdrCutoff, zscoreCutoff,
         ans <- lapply(seq_along(sampleChunks), function(idx){
             message(date(), ": Process chunk: ", idx, " for: ", type)
             sc <- sampleChunks[[idx]]
-            tmp_x <- object[,sc,,drop=FALSE]
+            tmp_x <- object[,sc]
 
             # extract values
             rawCts       <- as.matrix(K(tmp_x))
@@ -865,7 +865,7 @@ mapSeqlevels <- function(fds, style="UCSC", ...){
         nonSplicedReads(fds) <- keepStandardChromosomes(nonSplicedReads(fds))
         validObject(fds)
     }
-    fds <- fds[as.vector(seqnames(fds)) %in% names(mappings),,,drop=FALSE]
+    fds <- fds[as.vector(seqnames(fds)) %in% names(mappings)]
 
     seqlevels(fds) <- as.vector(mappings)
     seqlevels(nonSplicedReads(fds)) <- as.vector(mappings)

R/countRNAseqData.R

@@ -459,8 +459,8 @@ getSplitCountCacheFile <- function(sampleID, settings){
 #' @export
 countSplitReads <- function(sampleID, fds, NcpuPerSample=1, genome=NULL, 
                     recount=FALSE, keepNonStandardChromosomes=TRUE,
-                    bamfile=bamFile(fds[,sampleID,,drop=FALSE]),
-                    pairedend=pairedEnd(fds[,sampleID,,drop=FALSE]),
+                    bamfile=bamFile(fds[,sampleID]),
+                    pairedend=pairedEnd(fds[,sampleID]),
                     strandmode=strandSpecific(fds),
                     cacheFile=getSplitCountCacheFile(sampleID, fds),
                     scanbamparam=scanBamParam(fds),
@@ -856,11 +856,11 @@ countNonSplicedReads <- function(sampleID, splitCountRanges, fds,
     }
 
 
-    bamFile <- bamFile(fds[,samples(fds) == sampleID,,drop=FALSE])[[1]]
+    bamFile <- bamFile(fds[,samples(fds) == sampleID])[[1]]
 
     # unstranded case: for counting only non spliced reads we 
     # skip this information
-    isPairedEnd <- pairedEnd(fds[,samples(fds) == sampleID,,drop=FALSE])[[1]]
+    isPairedEnd <- pairedEnd(fds[,samples(fds) == sampleID])[[1]]
     doAutosort <- isPairedEnd
 
     # check cache if available

tests/testthat/helper_test_data.R

@@ -5,7 +5,7 @@ test_generate_count_example <- function(recount=FALSE){
     # get a new object for only one sample
     if(recount || !"test_fdsSample3" %in% ls()){
 
-        test_fdsSample3 <- getFraser()[,"sample3",,drop=FALSE]
+        test_fdsSample3 <- getFraser()[,"sample3"]
         name(test_fdsSample3) <- "onlySample3"
 
         # count the sample
@@ -22,7 +22,7 @@ test_generate_count_example <- function(recount=FALSE){
         end  =c(7592749, 7595171, 7595320)
     ))
     test_rangeOV  <- findOverlaps(test_range, test_fdsSample3, type = "equal")
-    test_rangeFDS <- test_fdsSample3[to(test_rangeOV),,,drop=FALSE]
+    test_rangeFDS <- test_fdsSample3[to(test_rangeOV)]
 
     #
     # This is manually counted from the IGV browser
@@ -51,7 +51,7 @@ test_generate_strand_specific_count_example <- function(recount=FALSE){
     if(recount || !"test_fdsSample3_stranded" %in% ls()){
 
         test_fdsSample3_stranded <- createTestFraserSettings(
-            workingDir=file.path(tempdir(), "strandSpecific"))[,"sample3",,drop=FALSE]
+            workingDir=file.path(tempdir(), "strandSpecific"))[,"sample3"]
         name(test_fdsSample3_stranded) <- "onlySample3_stranded"
         strandSpecific(test_fdsSample3_stranded) <- TRUE
         pairedEnd(test_fdsSample3_stranded) <- TRUE
@@ -72,7 +72,7 @@ test_generate_strand_specific_count_example <- function(recount=FALSE){
     test_rangeOV_stranded  <- findOverlaps(test_range_stranded, 
                                     test_fdsSample3_stranded, type = "equal")
     test_rangeFDS_stranded <- 
-        test_fdsSample3_stranded[to(test_rangeOV_stranded),,,drop=FALSE]
+        test_fdsSample3_stranded[to(test_rangeOV_stranded)]
 
     #
     # This is manually counted from the IGV browser 

vignettes/FRASER.Rnw

@@ -420,7 +420,7 @@ After looking at the expression distribution between filtered and unfiltered
 junctions, we can now subset the dataset:
 
 <<subset to filtered junctions, echo=TRUE>>=
-fds_filtered <- fds[mcols(fds, type="j")[,"passed"],,,drop=FALSE]
+fds_filtered <- fds[mcols(fds, type="j")[,"passed"]]
 fds_filtered
 # filtered_fds not further used for this tutorial because the example dataset
 # is otherwise too small