Remove the returnInterquantileWidth option.

Closes #114

NEWS.md

@@ -4,6 +4,8 @@ BACKWARDS-INCOMPATIBLE CHANGES
 
 -   Remove `CTSSclusteringMethod()` function and stop recording clustering
     method name.
+-   Remove `returnInterquantileWidth` argument of functions and always return
+    that width when quantile information is provided.  Closes #114
 
 NEW FEATURES
 

R/AggregationMethods.R

@@ -102,7 +102,7 @@ setMethod( "aggregateTagClusters", "CAGEr"
   # Prepare the GRangesList object containing the TCs.
   if (all( !is.null(qLow), !is.null(qUp))) {
    # If using quantiles, correct start and end.
-   TC.list <- tagClustersGR(object, returnInterquantileWidth = TRUE,  qLow = qLow, qUp = qUp)
+   TC.list <- tagClustersGR(object,  qLow = qLow, qUp = qUp)
    # Define start and and according to quantile positions.
    # Quantile coordinates are relative to start position: a value of "1" means
    # "first base of the cluster".  Therefore, 1 base must be subtracted in the

R/ExportMethods.R

@@ -264,7 +264,7 @@ setMethod( "plotInterquantileWidth", "CAGEexp"
 
   # Extract a list of data frames in "long" format for ggplot
 	iqwidths <- lapply(seq_along(sampleLabels(object)), function(x) {
-    gr <- getClustFun(object, x, returnInterquantileWidth = TRUE, qLow = qLow, qUp = qUp)
+    gr <- getClustFun(object, x, qLow = qLow, qUp = qUp)
     gr <- gr[score(gr) >= tpmThreshold]
     data.frame(
       sampleName  = sampleLabels(object)[[x]],
@@ -482,7 +482,7 @@ setMethod( "exportToTrack", "CAGEexp"
 	        , CTSS              = if (oneTrack) { CTSScoordinatesGR(object)
 	                              } else { CTSStagCountGR(object, samples = "all") }
 	        , tagClusters       = tagClustersGR(      object, qLow = qLow, qUp = qUp)
-	        , consensusClusters = consensusClustersGR(object, qLow = qLow, qUp = qUp, returnInterquantileWidth = ifelse(is.null(qLow), FALSE, TRUE))) # See issue 108
+	        , consensusClusters = consensusClustersGR(object, qLow = qLow, qUp = qUp))
 
 	exportToTrack( clusters, qLow = qLow, qUp = qUp
 	             , colorByExpressionProfile = colorByExpressionProfile

R/GetMethods.R

@@ -398,20 +398,17 @@ setMethod( "CTSSnormalizedTpmGR", "CAGEexp", function (object, samples) {
 #' extract tag clusters. If `samples = NULL`, a list of all the clusters for
 #' each sample is returned.
 #' 
-#' @param returnInterquantileWidth Return the interquantile width for each tag cluster.
-#' 
 #' @param qLow,qUp Position of which quantile should be used as a left (lower)
 #' or right (upper) boundary (for `qLow` and `qUp` respectively) when
 #' calculating interquantile width.  Default value `NULL` results in using the
-#' start coordinate of the cluster.  Used only when
-#' `returnInterquantileWidth = TRUE`, otherwise ignored.
+#' start coordinate of the cluster.
 #' 
 #' @return Returns a `GRangesList` or a `TagClusters` object with genomic coordinates,
 #' position of dominant TSS, total CAGE signal and additional information for
-#' all TCs from specified CAGE dataset (sample).  If
-#' `returnInterquantileWidth = TRUE`, interquantile width for each TC is also
-#' calculated using provided quantile positions.  The [`S4Vectors::metadata`]
-#' slot of the object contains a copy of the `CAGEexp` object's _column data_.
+#' all TCs from specified CAGE dataset (sample).  If quantile information is
+#' provided, interquantile width for each TC is also calculated.  The
+#' [`S4Vectors::metadata`] slot of the object contains a copy of the `CAGEexp`
+#' object's _column data_.
 #' 
 #' @author Vanja Haberle
 #' @author Charles Plessy
@@ -421,21 +418,18 @@ setMethod( "CTSSnormalizedTpmGR", "CAGEexp", function (object, samples) {
 #' @export
 #' 
 #' @examples
-#' tagClustersGR( exampleCAGEexp, "Zf.high", TRUE, 0.1, 0.9 )
-#' tagClustersGR( exampleCAGEexp, 1
-#'              , returnInterquantileWidth = TRUE, qLow = 0.1, qUp = 0.9 )
+#' tagClustersGR( exampleCAGEexp, "Zf.high", 0.1, 0.9 )
+#' tagClustersGR( exampleCAGEexp, 1, qLow = 0.1, qUp = 0.9 )
 #' tagClustersGR( exampleCAGEexp )@metadata$colData
 #' 
 #' @export
 
 setGeneric( "tagClustersGR"
-          , function( object, sample = NULL
-                    , returnInterquantileWidth = FALSE, qLow = NULL, qUp = NULL) {
+          , function( object, sample = NULL, qLow = NULL, qUp = NULL) {
   if (is.null(sample)) {
     tc.list <- GRangesList( lapply( sampleLabels(object)
                                   , tagClustersGR
                                   , object = object
-                                  , returnInterquantileWidth = returnInterquantileWidth
                                   , qLow = qLow, qUp = qUp))
     names(tc.list) <- sampleLabels(object)
     metadata(tc.list)$colData <- colData(object)
@@ -448,15 +442,12 @@ setGeneric( "tagClustersGR"
 #' @rdname tagClusters
 
 setMethod( "tagClustersGR", "CAGEexp"
-         , function (object, sample, returnInterquantileWidth, qLow, qUp) {
+         , function (object, sample, qLow, qUp) {
   tc <- metadata(object)$tagClusters[[sample]]
   if (is.null(tc))
     stop( "No clusters found, run ", sQuote("clusterCTSS"), " first." , call. = FALSE)
 
-  if (returnInterquantileWidth) {
-    if (is.null(qLow) | is.null(qUp))
-      stop( "No quantiles specified!  Set the ", sQuote("qLow")
-          , " and ", sQuote("qUp"), "arguments.")
+  if (! is.null(qLow) & ! is.null(qUp)) {
     qLowName <- paste0("q_", qLow)
     qUpName  <- paste0("q_", qUp)
     if(! all( c(qLowName, qUpName) %in% colnames(mcols(tc))))
@@ -487,20 +478,9 @@ setMethod("filteredCTSSidx", "CAGEexp", function (object){
 #' @param object A [`CAGEr`] object.
 #' 
 #' @param sample Optional. Label of the CAGE dataset (experiment, sample) for
-#'        which to extract sample-specific information on consensus clusters. 
-#'        When no sample is specified (NULL), sample-agnostic information 
-#'        on consensus clusters is provided. This includes the `dominant_ctss` 
-#'        and `tpm.dominant_ctss` for each consensus cluster.
-#' 
-#' @param returnInterquantileWidth Should the interquantile width of consensus
-#'        clusters be returned?  When `sample` argument is specified, the 
-#'        interquantile widths of the consensus clusters in that specified 
-#'        sample are returned, otherwise, the (sample-agnostic) interquantile 
-#'        width of the consensus cluster itself is returned.
+#'        which to extract sample-specific information on consensus clusters.
 #' 
-#' @param qLow,qUp Position of which quantile should be used as a left (lower)
-#'        or right (upper) boundary when calculating interquantile width.  Used
-#'        only when `returnInterquantileWidth = TRUE`, otherwise ignored.
+#' @param qLow,qUp Lower and upper quantiles to compute interquantile width.
 #' 
 #' @return `consensusClustersGR` returns a [`ConsensusClusters`] object, which
 #' wraps the [`GRanges`] class.  The `score` columns indicates the
@@ -510,10 +490,10 @@ setMethod("filteredCTSSidx", "CAGEexp", function (object){
 #' NOT specified, total CAGE signal across all CAGE datasets (samples) is
 #' returned in the `tpm` column.  When `sample` argument is specified, the `tpm`
 #' column contains CAGE signal of consensus clusters in that specific sample.
-#' When `returnInterquantileWidth = TRUE`, additional sample-specific information
-#' is returned, including position of the dominant TSS, and interquantile width
-#' of the consensus clusters in the specified sample or otherwise, 
-#' sample-agnostic information is returned.
+#' In addition, sample-specific information  is returned, including position of
+#' the dominant TSS, and (if applicable) interquantile width of the consensus
+#' clusters in the specified sample or otherwise, sample-agnostic information is
+#' returned.
 #' 
 #' @author Vanja Haberle
 #' @author Charles Plessy
@@ -525,24 +505,22 @@ setMethod("filteredCTSSidx", "CAGEexp", function (object){
 #' 
 #' @examples
 #' consensusClustersGR( exampleCAGEexp, sample = 2
-#'                    , returnInterquantileWidth = TRUE
 #'                    , qLow = 0.1, qUp = 0.9)
 #' 
 #' @importFrom GenomicRanges granges
 #' @export
 
 setGeneric( "consensusClustersGR"
           , function( object
-                    , sample = NULL
-                    , returnInterquantileWidth = FALSE
+                      , sample = NULL
                     , qLow = NULL, qUp = NULL) {
   validSamples(object, sample)
   standardGeneric("consensusClustersGR")})
 
 #' @rdname consensusClusters
 
 setMethod( "consensusClustersGR", "CAGEexp"
-         , function (object, sample, returnInterquantileWidth, qLow, qUp) {
+         , function (object, sample, qLow, qUp) {
   cc <- rowRanges(consensusClustersSE(object))
   ## Comment and edits added: 2022-OCT-06
   ## If sample is NULL, provide sample-agnostic information.
@@ -554,12 +532,9 @@ setMethod( "consensusClustersGR", "CAGEexp"
     if (!is.null(qUp))
       mcols(cc)[[paste0("q_", qUp)]]  <-
         consensusClustersQuantile(object, sample, qUp)
-    if (returnInterquantileWidth == TRUE) {
-      if (is.null(qLow) | is.null(qUp))
-        stop( "Set ", sQuote("qLow"), " and ", sQuote("qUp")
-            , " to specify the quantile positions used to calculate width.")
-      mcols(cc)[["interquantile_width"]] = mcols(cc)[[paste0("q_", qUp )]] -
-                                           mcols(cc)[[paste0("q_", qLow)]] + 1
+    if (! is.null(qLow) & ! is.null(qUp)) {
+    mcols(cc)[["interquantile_width"]] = mcols(cc)[[paste0("q_", qUp )]] -
+                                         mcols(cc)[[paste0("q_", qLow)]] + 1
     }
     cc$tpm <- cc$score <- consensusClustersTpm(object)[,sample]
 
@@ -570,7 +545,7 @@ setMethod( "consensusClustersGR", "CAGEexp"
     score(ctss) <- CTSSnormalizedTpmDF(object) |> rowSums.RleDataFrame()
     ctss <- ctss[ctss$filteredCTSSidx]
     cc <- .ctss_summary_for_clusters(ctss, cc, removeSingletons = FALSE)
-    if(isTRUE(returnInterquantileWidth)) {
+    if (! is.null(qLow) & ! is.null(qUp)) {
       qLowName <- paste0("q_", qLow)
       qUpName  <- paste0("q_", qUp)
       mcols(cc)[["interquantile_width"]] <- 

vignettes/CAGEexp.Rmd

@@ -544,8 +544,7 @@ ce <- quantilePositions(ce, clusters = "tagClusters", qLow = 0.1, qUp = 0.9)
 Tag clusters and their interquantile width can be retrieved by calling `tagClusters` function:
 
 ```{r}
-tagClustersGR( ce, "Zf.unfertilized.egg"
-             , returnInterquantileWidth = TRUE,  qLow = 0.1, qUp = 0.9)
+tagClustersGR(ce, "Zf.unfertilized.egg",  qLow = 0.1, qUp = 0.9)
 ```
 
 Once the cumulative distributions and the positions of quantiles have been calculated, the
@@ -608,17 +607,14 @@ different samples.  Sample-specific information on consensus clusters can be ret
 tag clusters):
 
 ```{r}
-consensusClustersGR( ce, sample = "Zf.unfertilized.egg"
-		               , returnInterquantileWidth = TRUE,  qLow = 0.1, qUp = 0.9)
+consensusClustersGR(ce, sample = "Zf.unfertilized.egg", qLow = 0.1, qUp = 0.9)
 ```
 
 This will, in addition to genomic coordinates of the consensus clusters, which are constant across all samples, also return the position of the dominant TSS, the CAGE signal (tpm) and the interquantile width specific for a given sample. Note that when specifying individual sample, only the consensus clusters that have some CAGE signal in that sample will be returned (which will be a subset of all consensus clusters).
 When setting `sample = NULL` sample-agnostic information per consensus cluster 
 is provided. 
 This includes the interquantile width and dominant TSS information for each 
-consensus cluster independent of the samples. 
-Again, specifying interquantile boundaries, qLow and qUp, has a similar 
-behaviour for `returnInterquantileWidth = TRUE`. 
+consensus cluster independent of the samples when specifying interquantile boundaries `qLow` and `qUp`.