@@ -1,7 +1,7 @@

 Package: chromstaR

 Type: Package

 Title: Combinatorial and Differential Chromatin State Analysis for ChIP-Seq Data

-Version: 1.6.0

+Version: 1.6.1

 Author: Aaron Taudt, Maria Colome Tatche, Matthias Heinig, Minh Anh Nguyen

 Maintainer: Aaron Taudt <aaron.taudt@gmail.com>

 Description: This package implements functions for combinatorial and differential analysis of ChIP-seq data. It includes uni- and multivariate peak-calling, export to genome browser viewable files, and functions for enrichment analyses.

@@ -59,6 +59,7 @@ importFrom(Rsamtools,indexBam)

 importFrom(Rsamtools,scanBamFlag)

 importFrom(S4Vectors,Rle)

 importFrom(S4Vectors,as.factor)

+importFrom(S4Vectors,endoapply)

 importFrom(S4Vectors,queryHits)

 importFrom(S4Vectors,runmean)

 importFrom(S4Vectors,subjectHits)

@@ -1,3 +1,21 @@

+CHANGES IN VERSION 1.6.1

+------------------------

+

+BUGFIXES

+

+    o Compatibility fixes for the new release of ggplot2 (3.0.0).

+    

+    o seqlevels() that are smaller than binsize are dropped properly in fixedWidthBins() and variableWidthBins().

+    

+    

+CHANGES IN VERSION 1.5.3

+------------------------

+

+SIGNIFICANT USER-LEVEL CHANGES

+

+    o Function 'changePostCutoff()' works on univariate peak calls without posterior needing to be present.

+    

+    

 CHANGES IN VERSION 1.5.1

 ------------------------

@@ -241,11 +241,13 @@ binReads <- function(file, experiment.table=NULL, ID=NULL, assembly, bamindex=fi

             if (format == 'bam' & use.bamsignals) {

                 ptm <- startTimedMessage("Counting overlaps for binsize ", binsize, " with offset ", offset, " ...")

+                suppressWarnings( # suppress warning due to offset over seqlength

                 bins.offset$counts <- tryCatch({

                     bins.offset$counts <- bamsignals::bamCount(file, bins.offset, mapqual=min.mapq, paired.end=paired.end, tlenFilter=c(0, max.fragment.width), verbose=FALSE)

                 }, error = function(err) {

                     bins.offset$counts <<- bamsignals::bamCount(file, bins.offset, mapqual=min.mapq, paired.end=paired.end, paired.end.max.frag.length=max.fragment.width, verbose=FALSE)

                 })

+                )

                 stopTimedMessage(ptm)

             } else {

@@ -6,6 +6,7 @@

 #' @param mode Mode of combination. See \code{\link{Chromstar}} for a description of the \code{mode} parameter.

 #' @return A \code{\link{combinedMultiHMM}} objects with combinatorial states for each condition.

 #' @author Aaron Taudt

+#' @importFrom S4Vectors endoapply

 #' @export

 #' @examples

 #'### Multivariate peak calling for spontaneous hypertensive rat (SHR) ###

@@ -277,7 +278,7 @@ combineMultivariates <- function(hmms, mode) {

     # Reassign levels such that all conditions have the same levels

     ptm <- startTimedMessage("Reassigning levels ...")

     comblevels <- sort(unique(unlist(lapply(combs.df, levels))))

-    combs.df <- endoapply(combs.df, function(x) { x <- factor(x, levels=comblevels) })

+    combs.df <- S4Vectors::endoapply(combs.df, function(x) { x <- factor(x, levels=comblevels) })

     names(combs.df) <- paste0('combination.', names(combs.df))

     stopTimedMessage(ptm)

@@ -28,6 +28,8 @@

 #'                 ranges=IRanges(start=genes$start, end=genes$end),

 #'                 strand=genes$strand,

 #'                 name=genes$external_gene_id, biotype=genes$gene_biotype)

+#'# Rename chrMT to chrM

+#'seqlevels(genes)[seqlevels(genes)=='chrMT'] <- 'chrM'

 #'print(genes)

 #'

 #'### Make the enrichment plots ###

@@ -227,10 +229,12 @@ plotFoldEnrichHeatmap <- function(hmm, annotations, what="combinations", combina

         minfold <- min(unlist(minfolds), na.rm=TRUE)

         limits <- max(abs(maxfold), abs(minfold))

         if (logscale) {

-            ggplts <- lapply(ggplts, function(ggplt) { ggplt + scale_fill_gradientn(name='log(observed/expected)', colors=grDevices::colorRampPalette(c("blue","white","red"))(20), values=c(seq(-limits,0,length.out=10), seq(0,limits,length.out=10)), rescaler=function(x,...) {x}, oob=identity, limits=c(-limits, limits)) })

+            # ggplts <- lapply(ggplts, function(ggplt) { ggplt + scale_fill_gradientn(name='log(observed/expected)', colors=grDevices::colorRampPalette(c("blue","white","red"))(20), values=c(seq(-limits,0,length.out=10), seq(0,limits,length.out=10)), rescaler=function(x,...) {x}, oob=identity, limits=c(-limits, limits)) }) # broke in ggplot2 3.0.0

+            ggplts <- lapply(ggplts, function(ggplt) { ggplt + scale_fill_gradientn(name='log(observed/expected)', colors=grDevices::colorRampPalette(c("blue","white","red"))(20), values=c(seq(-limits,0,length.out=10), seq(0,limits,length.out=10)), rescaler=function(x,...) {x}, limits=c(-limits, limits)) })

             ggplts <- lapply(ggplts, function(ggplt) { ggplt$data$foldEnrichment[ggplt$data$foldEnrichment == -Inf] <- -limits; ggplt })

         } else {

-            ggplts <- lapply(ggplts, function(ggplt) { ggplt + scale_fill_gradientn(name='observed/expected', colors=grDevices::colorRampPalette(c("blue","white","red"))(20), values=c(seq(0,1,length.out=10), seq(1,maxfold,length.out=10)), rescaler=function(x,...) {x}, oob=identity, limits=c(0,maxfold)) })

+            # ggplts <- lapply(ggplts, function(ggplt) { ggplt + scale_fill_gradientn(name='observed/expected', colors=grDevices::colorRampPalette(c("blue","white","red"))(20), values=c(seq(0,1,length.out=10), seq(1,maxfold,length.out=10)), rescaler=function(x,...) {x}, oob=identity, limits=c(0,maxfold)) }) # broke in ggplot2 3.0.0

+            ggplts <- lapply(ggplts, function(ggplt) { ggplt + scale_fill_gradientn(name='observed/expected', colors=grDevices::colorRampPalette(c("blue","white","red"))(20), values=c(seq(0,1,length.out=10), seq(1,maxfold,length.out=10)), rescaler=function(x,...) {x}, limits=c(0,maxfold)) })

         }

     }

@@ -95,11 +95,12 @@ fixedWidthBins <- function(bamfile=NULL, assembly=NULL, chrom.lengths=NULL, chro

         }

         seqlevels(bins) <- chroms2use

         seqlengths(bins) <- chrom.lengths[seqlevels(bins)]

+        skipped.chroms <- setdiff(chromosomes, as.character(unique(seqnames(bins))))

+        bins <- dropSeqlevels(bins, skipped.chroms, pruning.mode = 'coarse')

         bins.list[[as.character(binsize)]] <- bins

-        skipped.chroms <- setdiff(chromosomes, as.character(unique(seqnames(bins))))

         if (length(skipped.chroms)>0) {

-            warning("The following chromosomes were skipped because they are smaller than binsize ", binsize, ": ", paste0(skipped.chroms, collapse=', '))

+            warning("The following chromosomes were dropped because they are smaller than binsize ", binsize, ": ", paste0(skipped.chroms, collapse=', '))

         }

         stopTimedMessage(ptm)

@@ -121,6 +122,7 @@ fixedWidthBins <- function(bamfile=NULL, assembly=NULL, chrom.lengths=NULL, chro

 #' @param chromosomes A subset of chromosomes for which the bins are generated.

 #' @return A \code{list()} of \code{\link{GRanges-class}} objects with variable-width bins.

 #' @author Aaron Taudt

+#' @importFrom S4Vectors endoapply

 #' @export

 #'

 #'@examples

@@ -194,7 +196,7 @@ variableWidthBins <- function(reads, binsizes, chromosomes=NULL) {

             }

         }

         if (length(skipped.chroms)>0) {

-            warning("The following chromosomes were skipped because they are smaller than binsize ", binsize, ": ", paste0(skipped.chroms, collapse=', '))

+            warning("The following chromosomes were dropped because they are smaller than binsize ", binsize, ": ", paste0(skipped.chroms, collapse=', '))

         }

         subreads <- unlist(subreads, use.names=FALSE)

         ## Adjust length of reads to get consecutive bins

@@ -205,11 +207,11 @@ variableWidthBins <- function(reads, binsizes, chromosomes=NULL) {

         end(bins) <- end(bins) + 1

         ## We don't want incomplete bins at the end

         bins.split <- split(bins, seqnames(bins))

-        bins.split <- endoapply(bins.split, function(x) { x[-length(x)] })

+        bins.split <- S4Vectors::endoapply(bins.split, function(x) { x[-length(x)] })

         bins <- unlist(bins.split, use.names=FALSE)

         ## Remove skipped chromosomes

         bins <- bins[!seqnames(bins) %in% skipped.chroms]

-        bins <- keepSeqlevels(bins, setdiff(seqlevels(bins), skipped.chroms))

+        bins <- dropSeqlevels(bins, skipped.chroms, pruning.mode = 'coarse')

         bins.list[[as.character(binsize)]] <- bins

         stopTimedMessage(ptm)

@@ -87,6 +87,8 @@ genes <- GRanges(seqnames=paste0('chr',genes$chromosome_name),

                 ranges=IRanges(start=genes$start, end=genes$end),

                 strand=genes$strand,

                 name=genes$external_gene_id, biotype=genes$gene_biotype)

+# Rename chrMT to chrM

+seqlevels(genes)[seqlevels(genes)=='chrMT'] <- 'chrM'

 print(genes)

 ### Make the enrichment plots ###

@@ -389,7 +389,10 @@ genes <- GRanges(seqnames=paste0('chr',genes$chromosome_name),

                  ranges=IRanges(start=genes$start, end=genes$end),

                  strand=genes$strand,

                  name=genes$external_gene_id, biotype=genes$gene_biotype)

+# Rename chrMT to chrM to avoid warnings

 seqlevels(genes)[seqlevels(genes)=='chrMT'] <- 'chrM'

+# Select only chr12 to avoid warnings

+genes <- keepSeqlevels(genes, 'chr12', pruning.mode = 'coarse')

 print(genes)

 @

@@ -447,6 +450,7 @@ expression.SHR <- GRanges(seqnames=paste0('chr',expr$chromosome_name),

                           strand=expr$strand, name=expr$external_gene_id,

                           biotype=expr$gene_biotype,

                           expression=expr$expression_SHR)

+# Rename chrMT to chrM to avoid warnings

 seqlevels(expression.SHR)[seqlevels(expression.SHR)=='chrMT'] <- 'chrM'

 # We apply an asinh transformation to reduce the effect of outliers

 expression.SHR$expression <- asinh(expression.SHR$expression)

@@ -546,7 +550,10 @@ genes <- GRanges(seqnames=paste0('chr',genes$chromosome_name),

                  ranges=IRanges(start=genes$start, end=genes$end),

                  strand=genes$strand,

                  name=genes$external_gene_id, biotype=genes$gene_biotype)

+# Rename chrMT to chrM to avoid warnings

 seqlevels(genes)[seqlevels(genes)=='chrMT'] <- 'chrM'

+# Select only chr12 to avoid warnings

+genes <- keepSeqlevels(genes, 'chr12', pruning.mode = 'coarse')

 print(genes)

 @

Binary files a/vignettes/chromstaR.pdf and b/vignettes/chromstaR.pdf differ