@@ -38,4 +38,4 @@ License: Artistic-2.0

 LazyLoad: yes

 VignetteBuilder: knitr

 biocViews: ImmunoOncology, Software, DifferentialPeakCalling, HiddenMarkovModel, ChIPSeq, HistoneModification, MultipleComparison, Sequencing, PeakDetection, ATACSeq

-RoxygenNote: 6.0.1

+RoxygenNote: 7.1.0

@@ -49,7 +49,7 @@ import(chromstaRData)

 import(doParallel)

 import(foreach)

 import(ggplot2)

-importFrom(BiocGenerics, "%in%")

+importFrom(BiocGenerics,"%in%")

 importFrom(GenomicAlignments,first)

 importFrom(GenomicAlignments,readGAlignmentPairs)

 importFrom(GenomicAlignments,readGAlignments)

@@ -1,3 +1,11 @@

+CHANGES IN VERSION 1.14.1

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

+

+BUG FIXES

+

+    o Compatibility update: Replaced class() checks with is().

+

+

 CHANGES IN VERSION 1.13.1

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

@@ -45,7 +45,7 @@ binReads <- function(file, experiment.table=NULL, ID=NULL, assembly, bamindex=fi

         if (is.character(file)) {

             file.clean <- sub('\\.gz$','', file)

             format <- rev(strsplit(file.clean, '\\.')[[1]])[1]

-        } else if (class(file)=='GRanges') {

+        } else if (is(file,'GRanges')) {

             format <- 'GRanges'

         } else {

             stop("Could not determine format automatically. Please specify it via the 'format' parameter.")

@@ -59,11 +59,11 @@ binReads <- function(file, experiment.table=NULL, ID=NULL, assembly, bamindex=fi

     if (format=='bed') {

         temp <- assembly # trigger error if not defined

     }

-    if (class(bins) == 'GRanges') {

+    if (is(bins,'GRanges')) {

         bins <- list(bins)

         names(bins) <- width(bins[[1]])[1]

     }

-    if (class(bins) == 'list') {

+    if (is(bins,'list')) {

         if (is.null(names(bins))) {

             names(bins) <- sapply(bins, function(x) { width(x)[1] })

         }

@@ -177,7 +177,7 @@ binReads <- function(file, experiment.table=NULL, ID=NULL, assembly, bamindex=fi

         if (is.character(variable.width.reference)) {

             variable.width.reference.clean <- sub('\\.gz$','', variable.width.reference)

             vformat <- rev(strsplit(variable.width.reference.clean, '\\.')[[1]])[1]

-        } else if (class(variable.width.reference)=='GRanges') {

+        } else if (is(variable.width.reference,'GRanges')) {

             vformat <- 'GRanges'

         }

         if (vformat == 'bam') {

@@ -55,7 +55,7 @@ callPeaksMultivariate <- function(hmms, use.states, max.states=NULL, per.chrom=T

     ## Intercept user input

     if (!is.null(use.states)) {

-        if (class(use.states)!='data.frame') stop("argument 'use.states' expects a data.frame generated by function 'state.brewer'")

+        if (!is(use.states,'data.frame')) stop("argument 'use.states' expects a data.frame generated by function 'state.brewer'")

     }

     if (!is.null(max.states)) {

         if (check.positive.integer(max.states)!=0) stop("argument 'max.states' expects a positive integer")

@@ -45,7 +45,7 @@

 callPeaksReplicates <- function(hmm.list, max.states=32, force.equal=FALSE, eps=0.01, max.iter=NULL, max.time=NULL, keep.posteriors=TRUE, num.threads=1, max.distance=0.2, per.chrom=TRUE) {

     ## Enable reanalysis of multivariate HMM

-    if (class(hmm.list)==class.multivariate.hmm) {

+    if (is(hmm.list,class.multivariate.hmm)) {

         multimodel <- hmm.list

         if (is.null(multimodel$replicateInfo)) {

@@ -51,7 +51,7 @@

 #'

 callPeaksUnivariate <- function(binned.data, control.data=NULL, prefit.on.chr=NULL, short=TRUE, eps=0.1, init="standard", max.time=NULL, max.iter=5000, num.trials=1, eps.try=NULL, num.threads=1, read.cutoff=TRUE, read.cutoff.quantile=1, read.cutoff.absolute=500, max.mean=Inf, post.cutoff=0.5, control=FALSE, keep.posteriors=FALSE, keep.densities=FALSE, verbosity=1) {

-    if (class(binned.data) == 'character') { 

+    if (is(binned.data,'character')) { 

         messageU("Loading file(s) ", paste0(binned.data, collapse=', '), overline="_", underline=NULL)

         binned.datas <- loadHmmsFromFiles(binned.data)

         binned.data <- binned.datas[[1]]

@@ -66,7 +66,7 @@ callPeaksUnivariate <- function(binned.data, control.data=NULL, prefit.on.chr=NU

         }

     }

     if (!is.null(control.data)) {

-        if (class(control.data) == 'character') { 

+        if (is(control.data,'character')) { 

             message("Loading control file(s) ", paste0(control.data, collapse=', '))

             control.datas <- loadHmmsFromFiles(control.data)

             control.data <- control.datas[[1]]

@@ -168,7 +168,7 @@ callPeaksUnivariateAllChr <- function(binned.data, control.data=NULL, eps=0.01,

     war <- NULL

     if (is.null(eps.try)) eps.try <- eps

     ## Load binned.data and reuse values if present

-    if (class(binned.data) == 'character') { 

+    if (is(binned.data,'character')) { 

         binned.data <- loadHmmsFromFiles(binned.data)[[1]]

     }

@@ -182,7 +182,7 @@ callPeaksUnivariateAllChr <- function(binned.data, control.data=NULL, eps=0.01,

     info <- attr(binned.data, 'info')

     ### Assign initial parameters ###

-    if (class(binned.data) == class.univariate.hmm) {

+    if (is(binned.data,class.univariate.hmm)) {

         message("Using parameters from univariate HMM")

         hmm <- binned.data

         binned.data <- hmm$bins

@@ -194,7 +194,7 @@ callPeaksUnivariateAllChr <- function(binned.data, control.data=NULL, eps=0.01,

         size.initial <- hmm$distributions$size

         prob.initial <- hmm$distributions$prob

         continue.from.univariate.hmm <- TRUE

-    } else if (class(binned.data) == 'GRanges') {

+    } else if (is(binned.data,'GRanges')) {

         A.initial <- double(length=numstates*numstates)

         proba.initial <- double(length=numstates)

         size.initial <- double(length=numstates)

@@ -48,7 +48,7 @@ dec2bin = function(dec, colnames=NULL, ndigits=NULL) {

             binary.states[ ,ncol(binary.states)+1-i1] <- modulos[[i1]]

         }

     }

-    if (class(binary.states)!='matrix') {

+    if (!is(binary.states, 'matrix')) {

         binary.states <- matrix(binary.states, nrow=length(dec))

     }

@@ -78,8 +78,8 @@ plotFoldEnrichHeatmap <- function(hmm, annotations, what="combinations", combina

     hmm <- loadHmmsFromFiles(hmm, check.class=c(class.multivariate.hmm, class.combined.multivariate.hmm))[[1]]

     ## Variables

     bins <- hmm$bins

-    if (class(hmm) == class.combined.multivariate.hmm) {

-    } else if (class(hmm) == class.multivariate.hmm) {

+    if (is(hmm,class.combined.multivariate.hmm)) {

+    } else if (is(hmm,class.multivariate.hmm)) {

         # Rename 'combination' to 'combination.' for coherence with combinedMultiHMM

         names(mcols(bins))[grep('combination', names(mcols(bins)))] <- paste0('combination.', unique(hmm$info$condition))

     }

@@ -238,13 +238,13 @@ plotFoldEnrichHeatmap <- function(hmm, annotations, what="combinations", combina

         }

     }

-    if (class(hmm) == class.multivariate.hmm | what == 'transitions') {

+    if (is(hmm,class.multivariate.hmm) | what == 'transitions') {

         if (plot) {

             return(ggplts[[1]])

         } else {

             return(folds[[1]])

         }

-    } else if (class(hmm) == class.combined.multivariate.hmm) {

+    } else if (is(hmm,class.combined.multivariate.hmm)) {

         if (plot) {

             return(ggplts)

         } else {

@@ -273,7 +273,7 @@ plotEnrichCountHeatmap <- function(hmm, annotation, bp.around.annotation=10000,

     hmm <- loadHmmsFromFiles(hmm, check.class=c(class.multivariate.hmm, class.combined.multivariate.hmm))[[1]]

     ## Variables

     bins <- hmm$bins

-    if (class(hmm) == class.combined.multivariate.hmm) {

+    if (is(hmm,class.combined.multivariate.hmm)) {

         conditions <- sub('combination.', '', grep('combination', names(mcols(bins)), value=TRUE))

         comb.levels <- levels(mcols(bins)[,paste0('combination.', conditions[1])])

         ## Create new column combination with all conditions combined

@@ -283,7 +283,7 @@ plotEnrichCountHeatmap <- function(hmm, annotation, bp.around.annotation=10000,

         }

         combs$sep <- ', '

         bins$combination <- factor(do.call(paste, combs))

-    } else if (class(hmm) == class.multivariate.hmm) {

+    } else if (is(hmm,class.multivariate.hmm)) {

         comb.levels <- levels(bins$combination)

     }

     binsize <- width(bins)[1]

@@ -430,14 +430,14 @@ plotEnrichment <- function(hmm, annotation, bp.around.annotation=10000, region=c

     ## Variables

     hmm <- loadHmmsFromFiles(hmm, check.class=c(class.univariate.hmm, class.multivariate.hmm, class.combined.multivariate.hmm))[[1]]

     bins <- hmm$bins

-    if (class(hmm) == class.univariate.hmm) {

+    if (is(hmm,class.univariate.hmm)) {

         # bins$counts <- rpkm.vector(hmm$bins$counts, binsize=mean(width(hmm$bins)))

         mcols(bins)['combination.'] <- bins$state

         bins$state <- c('zero-inflation' = 0, 'unmodified' = 0, 'modified' = 1)[bins$state]

         hmm$info <- data.frame(file=NA, mark=1, condition=1, replicate=1, pairedEndReads=NA, controlFiles=NA, ID='1-1-rep1')

-    } else if (class(hmm) == class.combined.multivariate.hmm) {

+    } else if (is(hmm,class.combined.multivariate.hmm)) {

         # bins$counts <- rpkm.matrix(hmm$bins$counts, binsize=mean(width(hmm$bins)))

-    } else if (class(hmm) == class.multivariate.hmm) {

+    } else if (is(hmm,class.multivariate.hmm)) {

         # bins$counts <- rpkm.matrix(hmm$bins$counts, binsize=mean(width(hmm$bins)))

         # Rename 'combination' to 'combination.' for coherence with combinedMultiHMM

         names(mcols(bins))[grep('combination', names(mcols(bins)))] <- 'combination.'

@@ -566,11 +566,11 @@ plotEnrichment <- function(hmm, annotation, bp.around.annotation=10000, region=c

         ggplts <- lapply(ggplts, function(ggplt) { ggplt + scale_y_continuous(limits=c(minfold*(1-sign(minfold)*0.1),maxfold*(1+sign(maxfold)*0.1))) })

     }

     ggplts <- lapply(ggplts, function(ggplt) { ggplt + scale_color_manual(values=getDistinctColors(maxcol)) }) # Add color here like this because of weird bug

-    if (class(hmm) == class.univariate.hmm) {

+    if (is(hmm,class.univariate.hmm)) {

         return(ggplts[[1]])

-    } else if (class(hmm) == class.multivariate.hmm) {

+    } else if (is(hmm,class.multivariate.hmm)) {

         return(ggplts[[1]])

-    } else if (class(hmm) == class.combined.multivariate.hmm) {

+    } else if (is(hmm,class.combined.multivariate.hmm)) {

         return(ggplts)

     }

@@ -26,13 +26,13 @@ NULL

 exportPeaks <- function(model, filename, header=TRUE, separate.files=TRUE, trackname=NULL) {

     model <- loadHmmsFromFiles(model)[[1]]

-    if (class(model) == class.univariate.hmm) {

+    if (is(model,class.univariate.hmm)) {

         exportUnivariatePeaks(list(model), filename=paste0(filename, '_peaks'), header=header, separate.files=separate.files, trackname=trackname)

     }

-    if (class(model) == class.multivariate.hmm) {

+    if (is(model,class.multivariate.hmm)) {

         exportMultivariatePeaks(model, filename=paste0(filename, '_peaks'), header=header, separate.files=separate.files, trackname=trackname)

     }

-    if (class(model) == class.combined.multivariate.hmm) {

+    if (is(model,class.combined.multivariate.hmm)) {

         exportCombinedMultivariatePeaks(model, filename=paste0(filename, '_peaks'), header=header, separate.files=separate.files, trackname=trackname)

     }

@@ -44,16 +44,16 @@ exportPeaks <- function(model, filename, header=TRUE, separate.files=TRUE, track

 exportCounts <- function(model, filename, header=TRUE, separate.files=TRUE, trackname=NULL) {

     model <- loadHmmsFromFiles(model)[[1]]

-    if (class(model) == 'GRanges') {

+    if (is(model,'GRanges')) {

         exportBinnedData(list(model), filename=paste0(filename, '_counts'), header=header, separate.files=separate.files, trackname=trackname)

     }

-    if (class(model) == class.univariate.hmm) {

+    if (is(model,class.univariate.hmm)) {

         exportUnivariateCounts(list(model), filename=paste0(filename, '_counts'), header=header, separate.files=separate.files, trackname=trackname)

     }

-    if (class(model) == class.multivariate.hmm) {

+    if (is(model,class.multivariate.hmm)) {

         exportMultivariateCounts(model, filename=paste0(filename, '_counts'), header=header, separate.files=separate.files, trackname=trackname)

     }

-    if (class(model) == class.combined.multivariate.hmm) {

+    if (is(model,class.combined.multivariate.hmm)) {

         exportCombinedMultivariateCounts(model, filename=paste0(filename, '_counts'), header=header, separate.files=separate.files, trackname=trackname)

     }

@@ -67,10 +67,10 @@ exportCounts <- function(model, filename, header=TRUE, separate.files=TRUE, trac

 exportCombinations <- function(model, filename, header=TRUE, separate.files=TRUE, trackname=NULL, exclude.states='[]', include.states=NULL) {

     model <- loadHmmsFromFiles(model)[[1]]

-    if (class(model) == class.multivariate.hmm) {

+    if (is(model,class.multivariate.hmm)) {

         exportMultivariateCombinations(model, filename=paste0(filename, '_combinations'), header=header, trackname=trackname, exclude.states=exclude.states, include.states=include.states)

     }

-    if (class(model) == class.combined.multivariate.hmm) {

+    if (is(model,class.combined.multivariate.hmm)) {

         exportCombinedMultivariateCombinations(model, filename=paste0(filename, '_combinations'), header=header, separate.files=separate.files, trackname=trackname, exclude.states=exclude.states, include.states=include.states)

     }

@@ -52,8 +52,8 @@ plotExpression <- function(hmm, expression, combinations=NULL, return.marks=FALS

     hmm <- loadHmmsFromFiles(hmm, check.class=c(class.multivariate.hmm, class.combined.multivariate.hmm))[[1]]

     ## Variables

     bins <- hmm$bins

-    if (class(hmm) == class.combined.multivariate.hmm) {

-    } else if (class(hmm) == class.multivariate.hmm) {

+    if (is(hmm,class.combined.multivariate.hmm)) {

+    } else if (is(hmm,class.multivariate.hmm)) {

         # Rename 'combination' to 'combination.' for coherence with combinedMultiHMM

         names(mcols(bins))[grep('combination', names(mcols(bins)))] <- paste0('combination.', unique(hmm$info$condition))

     }

@@ -95,9 +95,9 @@ plotExpression <- function(hmm, expression, combinations=NULL, return.marks=FALS

         ggplts[[condition]] <- ggplt

     }

-    if (class(hmm) == class.multivariate.hmm) {

+    if (is(hmm,class.multivariate.hmm)) {

         return(ggplts[[1]])

-    } else if (class(hmm) == class.combined.multivariate.hmm) {

+    } else if (is(hmm,class.combined.multivariate.hmm)) {

         return(ggplts)

     }

@@ -30,7 +30,7 @@ genomicFrequencies <- function(multi.hmm, combinations=NULL, per.mark=FALSE) {

         return(list(frequency=t, domains=s))

     }

-    if (class(multi.hmm)==class.multivariate.hmm) {

+    if (is(multi.hmm,class.multivariate.hmm)) {

         if (is.null(combinations)) {

             comb.levels <- levels(bins$combination)

@@ -43,7 +43,7 @@ genomicFrequencies <- function(multi.hmm, combinations=NULL, per.mark=FALSE) {

         s <- s[names(s) %in% comb.levels]

         return(list(frequency=t, domains=s))

-    } else if (class(multi.hmm)==class.combined.multivariate.hmm) {

+    } else if (is(multi.hmm,class.combined.multivariate.hmm)) {

         if (is.null(combinations)) {

             comb.levels <- unique(as.vector(sapply(getCombinations(bins), levels)))

@@ -32,7 +32,7 @@ readBamFileAsGRanges <- function(bamfile, bamindex=bamfile, chromosomes=NULL, pa

     ## Input checks

     if (!is.null(blacklist)) {

-        if ( !(is.character(blacklist) | class(blacklist)=='GRanges') ) {

+        if ( !(is.character(blacklist) | is(blacklist,'GRanges')) ) {

             stop("'blacklist' has to be either a bed(.gz) file or a GRanges object")

         }

     }

@@ -141,7 +141,7 @@ readBamFileAsGRanges <- function(bamfile, bamindex=bamfile, chromosomes=NULL, pa

                 chromosome.format <- 'NCBI'

             }

             black <- readCustomBedFile(blacklist, skip=0, chromosome.format=chromosome.format)

-        } else if (class(blacklist)=='GRanges') {

+        } else if (is(blacklist,'GRanges')) {

             black <- blacklist

         } else {

             stop("'blacklist' has to be either a bed(.gz) file or a GRanges object")

@@ -206,7 +206,7 @@ readBedFileAsGRanges <- function(bedfile, assembly, chromosomes=NULL, remove.dup

     ## Input checks

     if (!is.null(blacklist)) {

-        if ( !(is.character(blacklist) | class(blacklist)=='GRanges') ) {

+        if ( !(is.character(blacklist) | is(blacklist,'GRanges')) ) {

             stop("'blacklist' has to be either a bed(.gz) file or a GRanges object")

         }

     }

@@ -311,7 +311,7 @@ readBedFileAsGRanges <- function(bedfile, assembly, chromosomes=NULL, remove.dup

                 chromosome.format <- 'NCBI'

             }

             black <- readCustomBedFile(blacklist, skip=0, chromosome.format=chromosome.format)

-        } else if (class(blacklist)=='GRanges') {

+        } else if (is(blacklist,'GRanges')) {

             black <- blacklist

         } else {

             stop("'blacklist' has to be either a bed(.gz) file or a GRanges object")

@@ -175,7 +175,7 @@ variableWidthBins <- function(reads, binsizes, chromosomes=NULL) {

     for (i1 in 1:length(binsizes)) {

         binsize <- binsizes[i1]

         ptm <- startTimedMessage("Making variable-width windows for bin size ", binsize, " ...")

-        if (class(binned.list)=='GRanges') {

+        if (is(binned.list,'GRanges')) {

             binned <- binned.list

         } else {

             binned <- binned.list[[i1]]

@@ -10,7 +10,7 @@ getMaxPostInPeaks <- function(states, posteriors) {

         r$values[r$values == FALSE] <- NA

         peakNumbers <- inverse.rle(r)

         df <- aggregate(posteriors[,icol], by=list(peakNumber=peakNumbers), FUN=max)

-        if (class(df$x) == 'list') {

+        if (is(df$x,'list')) {

             class(df$x) <- 'numeric'

         }

         r <- r.bin

@@ -477,7 +477,7 @@ plotGenomeBrowser <- function(model, chr, start, end, style='peaks', peakHeight=

     bins <- model$bins

     ranges2plot <- reduce(bins[bins@seqnames == chr & start(bins) >= start & start(bins) <= end, , drop=FALSE])

     bins <- subsetByOverlaps(bins, ranges2plot)

-    if (class(model)=='uniHMM') {

+    if (is(model,'uniHMM')) {

         peaklist <- list(model$peaks)

         bins$counts.rpkm <- matrix(bins$counts.rpkm, ncol=1)

         if (is.null(model$info)) {

@@ -61,7 +61,7 @@ removeCondition <- function(model, conditions) {

         removeconds <- paste0(paste0('-', conditions, '-'), collapse='|')

         keepconds <- grep(removeconds, colnames(counts), invert=TRUE, value=TRUE)

         counts <- counts[,keepconds]

-        if (class(counts) != "matrix") {

+        if (!is(counts,'matrix')) {

             counts <- matrix(counts, ncol=1, dimnames=list(NULL, keepconds))

         }

         model$bins$counts.rpkm <- counts

@@ -71,7 +71,7 @@ removeCondition <- function(model, conditions) {

         removeconds <- paste0(paste0('-', conditions, '-'), collapse='|')

         keepconds <- grep(removeconds, colnames(posteriors), invert=TRUE, value=TRUE)

         posteriors <- posteriors[,keepconds]

-        if (class(posteriors) != "matrix") {

+        if (!is(posteriors,'matrix')) {

             posteriors <- matrix(posteriors, ncol=1, dimnames=list(NULL, keepconds))

         }

         model$bins$posteriors <- posteriors

@@ -81,7 +81,7 @@ removeCondition <- function(model, conditions) {

         removeconds <- paste0(paste0('-', conditions, '-'), collapse='|')

         keepconds <- grep(removeconds, colnames(maxPostInPeak), invert=TRUE, value=TRUE)

         maxPostInPeak <- maxPostInPeak[,keepconds]

-        if (class(maxPostInPeak) != "matrix") {

+        if (!is(maxPostInPeak,'matrix')) {

             maxPostInPeak <- matrix(maxPostInPeak, ncol=1, dimnames=list(NULL, keepconds))

         }

         model$bins$maxPostInPeak <- maxPostInPeak

@@ -148,7 +148,7 @@ state.brewer <- function(replicates=NULL, differential.states=FALSE, min.diff=1,

         }

     }

     if (!is.null(binary.matrix)) {

-        if (class(binary.matrix) != 'matrix' | mode(binary.matrix) != 'logical') {

+        if (!is(binary.matrix,'matrix') | mode(binary.matrix) != 'logical') {

             stop("argument 'binary.matrix' expects a logical matrix")

         }

     }

@@ -197,11 +197,11 @@ state.brewer <- function(replicates=NULL, differential.states=FALSE, min.diff=1,

         statenames.sep <- apply(as.matrix(binstates[,mask]), 1, function(x) { tracknames.mask[x] })

         if (length(statenames.sep)==0) {

             stop("Something went wrong in constructing state names.")

-        } else if (class(statenames.sep)=='list') {

+        } else if (is(statenames.sep,'list')) {

             statenames <- sapply(statenames.sep, paste, collapse=sep)

-        } else if (class(statenames.sep)=='matrix') {

+        } else if (is(statenames.sep,'matrix')) {

             statenames <- apply(statenames.sep, 2, paste, collapse=sep)

-        } else if (class(statenames.sep)=='character') {

+        } else if (is(statenames.sep,'character')) {

             statenames <- statenames.sep

         }

     } else {

@@ -245,7 +245,7 @@ state.brewer <- function(replicates=NULL, differential.states=FALSE, min.diff=1,

                     mask <- rowSums(as.matrix(binstates[,names[track.index]]), na.rm = TRUE) < 2

                     binstates <- binstates[mask,]

-                    if (class(binstates)!='matrix') {

+                    if (!is(binstates,'matrix')) {

                         binstates <- matrix(binstates, ncol=numtracks)

                         colnames(binstates) <- tracknames

                     }

@@ -267,7 +267,7 @@ state.brewer <- function(replicates=NULL, differential.states=FALSE, min.diff=1,

                 mask <- rep(TRUE, nrow(binstates))

             }

             binstates <- binstates[mask,]

-            if (class(binstates)!='matrix') {

+            if (!is(binstates,'matrix')) {

                 binstates <- matrix(binstates, ncol=length(binstates))

                 colnames(binstates) <- tracknames

             }

@@ -288,7 +288,7 @@ state.brewer <- function(replicates=NULL, differential.states=FALSE, min.diff=1,

         bindiffmatrix <- dec2bin(0:(2^length(intersect.tracks)-1)) # all possible binary combinations (rows) between tracks (cols)

         controlsum <- apply(bindiffmatrix, 1, sum)

         bindiffmatrix <- bindiffmatrix[controlsum >= min.diff,]

-        if (class(bindiffmatrix)!='matrix') { # R-behaviour differs with only one column

+        if (!is(bindiffmatrix,'matrix')) { # R-behaviour differs with only one column

             bindiffmatrix <- matrix(bindiffmatrix, nrow=1)

         }

         colnames(bindiffmatrix) <- intersect.tracks

@@ -338,7 +338,7 @@ state.brewer <- function(replicates=NULL, differential.states=FALSE, min.diff=1,

                     mask <- rep(TRUE, nrow(binstates.irow))

                 }

                 binstates.irow <- binstates.irow[mask,]

-                if (class(binstates.irow)!='matrix') {

+                if (!is(binstates.irow,'matrix')) {

                     binstates.irow <- matrix(binstates.irow, ncol=length(binstates.irow))

                     colnames(binstates.irow) <- tracknames.conditions

                 }

@@ -363,7 +363,7 @@ state.brewer <- function(replicates=NULL, differential.states=FALSE, min.diff=1,

         tracks2compare.split <- split(tracks2compare, conditions)

         intersect.tracks <- Reduce(intersect, lapply(tracks2compare.split, unique))

         bincommonmatrix <- dec2bin(0:(2^length(intersect.tracks)-1)) # all possible binary combinations (rows) between tracks (cols)

-        if (class(bincommonmatrix)!='matrix') { # R-behaviour differs with only one column

+        if (!is(bincommonmatrix,'matrix')) { # R-behaviour differs with only one column

             bincommonmatrix <- matrix(bincommonmatrix, nrow=1)

         }

         colnames(bincommonmatrix) <- intersect.tracks

@@ -411,7 +411,7 @@ state.brewer <- function(replicates=NULL, differential.states=FALSE, min.diff=1,

                     mask <- apply(as.matrix(binstates.irow[,track.index]), 1, function(x) { Reduce('&', x) })

                 }

                 binstates.irow <- binstates.irow[mask,]

-                if (class(binstates.irow)!='matrix') {

+                if (!is(binstates.irow,'matrix')) {

                     binstates.irow <- matrix(binstates.irow, ncol=length(binstates.irow))

                     colnames(binstates.irow) <- tracknames.conditions

                 }

@@ -435,11 +435,11 @@ state.brewer <- function(replicates=NULL, differential.states=FALSE, min.diff=1,

         statenames.sep <- apply(as.matrix(binstates[,mask]), 1, function(x) { tracknames.mask[x] })

         if (length(statenames.sep)==0) {

             stop("Something went wrong in constructing state names.")

-        } else if (class(statenames.sep)=='list') {

+        } else if (is(statenames.sep,'list')) {

             statenames <- sapply(statenames.sep, paste, collapse=sep)

-        } else if (class(statenames.sep)=='matrix') {

+        } else if (is(statenames.sep,'matrix')) {

             statenames <- apply(statenames.sep, 2, paste, collapse=sep)

-        } else if (class(statenames.sep)=='character') {

+        } else if (is(statenames.sep,'character')) {

             statenames <- statenames.sep

         }

     } else {

@@ -4,13 +4,31 @@

 \alias{Chromstar}

 \title{Wrapper function for the \pkg{\link{chromstaR}} package}

 \usage{

-Chromstar(inputfolder, experiment.table, outputfolder, configfile = NULL,

-  numCPU = 1, binsize = 1000, stepsize = binsize/2, assembly = NULL,

-  chromosomes = NULL, remove.duplicate.reads = TRUE, min.mapq = 10,

-  format = NULL, prefit.on.chr = NULL, eps.univariate = 0.1,

-  max.time = NULL, max.iter = 5000, read.cutoff.absolute = 500,

-  keep.posteriors = TRUE, mode = "differential", max.states = 128,

-  per.chrom = TRUE, eps.multivariate = 0.01, exclusive.table = NULL)

+Chromstar(

+  inputfolder,

+  experiment.table,

+  outputfolder,

+  configfile = NULL,

+  numCPU = 1,

+  binsize = 1000,

+  stepsize = binsize/2,

+  assembly = NULL,

+  chromosomes = NULL,

+  remove.duplicate.reads = TRUE,

+  min.mapq = 10,

+  format = NULL,

+  prefit.on.chr = NULL,

+  eps.univariate = 0.1,

+  max.time = NULL,

+  max.iter = 5000,

+  read.cutoff.absolute = 500,

+  keep.posteriors = TRUE,

+  mode = "differential",

+  max.states = 128,

+  per.chrom = TRUE,

+  eps.multivariate = 0.01,

+  exclusive.table = NULL

+)

 }

 \arguments{

 \item{inputfolder}{Folder with either BAM or BED-6 (see \code{\link{readBedFileAsGRanges}} files.}

@@ -27,7 +45,7 @@ Chromstar(inputfolder, experiment.table, outputfolder, configfile = NULL,

 \item{stepsize}{An integer specifying the step size for analysis.}

-\item{assembly}{A \code{data.frame} or tab-separated file with columns 'chromosome' and 'length'. Alternatively a character specifying the assembly, see \code{\link[GenomeInfoDb]{fetchExtendedChromInfoFromUCSC}} for available assemblies. Specifying an assembly is only necessary when importing BED files. BAM files are handled automatically.}

+\item{assembly}{A \code{data.frame} or tab-separated file with columns 'chromosome' and 'length'. Alternatively a character specifying the assembly, see \code{\link[GenomeInfoDb]{getChromInfoFromUCSC}} for available assemblies. Specifying an assembly is only necessary when importing BED files. BAM files are handled automatically.}

 \item{chromosomes}{If only a subset of the chromosomes should be imported, specify them here.}

@@ -5,12 +5,26 @@

 \alias{binning}

 \title{Convert aligned reads from various file formats into read counts in equidistant bins}

 \usage{

-binReads(file, experiment.table = NULL, ID = NULL, assembly,

-  bamindex = file, chromosomes = NULL, pairedEndReads = FALSE,

-  min.mapq = 10, remove.duplicate.reads = TRUE, max.fragment.width = 1000,

-  blacklist = NULL, binsizes = 1000, stepsizes = binsizes/2,

-  reads.per.bin = NULL, bins = NULL, variable.width.reference = NULL,

-  use.bamsignals = TRUE, format = NULL)

+binReads(

+  file,

+  experiment.table = NULL,

+  ID = NULL,

+  assembly,

+  bamindex = file,

+  chromosomes = NULL,

+  pairedEndReads = FALSE,

+  min.mapq = 10,

+  remove.duplicate.reads = TRUE,

+  max.fragment.width = 1000,

+  blacklist = NULL,

+  binsizes = 1000,

+  stepsizes = binsizes/2,

+  reads.per.bin = NULL,

+  bins = NULL,

+  variable.width.reference = NULL,

+  use.bamsignals = TRUE,

+  format = NULL

+)

 }

 \arguments{

 \item{file}{A file with aligned reads. Alternatively a \code{\link{GRanges-class}} with aligned reads.}

@@ -19,7 +33,7 @@ binReads(file, experiment.table = NULL, ID = NULL, assembly,

 \item{ID}{Optional ID to select a row from the \code{experiment.table}. Only necessary if the experiment table contains the same file in multiple positions in column 'file'.}

-\item{assembly}{Please see \code{\link[GenomeInfoDb]{fetchExtendedChromInfoFromUCSC}} for available assemblies. Only necessary when importing BED files. BAM files are handled automatically. Alternatively a data.frame with columns 'chromosome' and 'length'.}

+\item{assembly}{Please see \code{\link[GenomeInfoDb]{getChromInfoFromUCSC}} for available assemblies. Only necessary when importing BED files. BAM files are handled automatically. Alternatively a data.frame with columns 'chromosome' and 'length'.}

 \item{bamindex}{BAM index file. Can be specified without the .bai ending. If the index file does not exist it will be created and a warning is issued.}

@@ -4,10 +4,21 @@

 \alias{callPeaksMultivariate}

 \title{Fit a Hidden Markov Model to multiple ChIP-seq samples}

 \usage{

-callPeaksMultivariate(hmms, use.states, max.states = NULL, per.chrom = TRUE,

-  chromosomes = NULL, eps = 0.01, keep.posteriors = FALSE,

-  num.threads = 1, max.time = NULL, max.iter = NULL,

-  keep.densities = FALSE, verbosity = 1, temp.savedir = NULL)

+callPeaksMultivariate(

+  hmms,

+  use.states,

+  max.states = NULL,

+  per.chrom = TRUE,

+  chromosomes = NULL,

+  eps = 0.01,

+  keep.posteriors = FALSE,

+  num.threads = 1,

+  max.time = NULL,

+  max.iter = NULL,

+  keep.densities = FALSE,

+  verbosity = 1,

+  temp.savedir = NULL

+)

 }

 \arguments{

 \item{hmms}{A list of \code{\link{uniHMM}}s generated by \code{\link{callPeaksUnivariate}}, e.g. \code{list(hmm1,hmm2,...)} or a vector of files that contain such objects, e.g. \code{c("file1","file2",...)}.}

@@ -4,9 +4,18 @@

 \alias{callPeaksReplicates}

 \title{Fit a multivariate Hidden Markov Model to multiple ChIP-seq replicates}

 \usage{

-callPeaksReplicates(hmm.list, max.states = 32, force.equal = FALSE,

-  eps = 0.01, max.iter = NULL, max.time = NULL, keep.posteriors = TRUE,

-  num.threads = 1, max.distance = 0.2, per.chrom = TRUE)

+callPeaksReplicates(

+  hmm.list,

+  max.states = 32,

+  force.equal = FALSE,

+  eps = 0.01,

+  max.iter = NULL,

+  max.time = NULL,

+  keep.posteriors = TRUE,

+  num.threads = 1,

+  max.distance = 0.2,

+  per.chrom = TRUE

+)

 }

 \arguments{

 \item{hmm.list}{A list of \code{\link{uniHMM}}s generated by \code{\link{callPeaksUnivariate}}, e.g. \code{list(hmm1,hmm2,...)} or \code{c("file1","file2",...)}. Alternatively, this parameter also accepts a \code{\link{multiHMM}} and will check if the distance between replicates is greater than \code{max.distance}.}

@@ -4,13 +4,28 @@

 \alias{callPeaksUnivariate}

 \title{Fit a Hidden Markov Model to a ChIP-seq sample.}

 \usage{

-callPeaksUnivariate(binned.data, control.data = NULL, prefit.on.chr = NULL,

-  short = TRUE, eps = 0.1, init = "standard", max.time = NULL,

-  max.iter = 5000, num.trials = 1, eps.try = NULL, num.threads = 1,

-  read.cutoff = TRUE, read.cutoff.quantile = 1,

-  read.cutoff.absolute = 500, max.mean = Inf, post.cutoff = 0.5,

-  control = FALSE, keep.posteriors = FALSE, keep.densities = FALSE,

-  verbosity = 1)

+callPeaksUnivariate(

+  binned.data,

+  control.data = NULL,

+  prefit.on.chr = NULL,

+  short = TRUE,

+  eps = 0.1,

+  init = "standard",

+  max.time = NULL,

+  max.iter = 5000,

+  num.trials = 1,

+  eps.try = NULL,

+  num.threads = 1,

+  read.cutoff = TRUE,

+  read.cutoff.quantile = 1,

+  read.cutoff.absolute = 500,

+  max.mean = Inf,

+  post.cutoff = 0.5,

+  control = FALSE,

+  keep.posteriors = FALSE,

+  keep.densities = FALSE,

+  verbosity = 1

+)

 }

 \arguments{

 \item{binned.data}{A \code{\link{GRanges-class}} object with binned read counts or a file that contains such an object.}

@@ -4,12 +4,26 @@

 \alias{callPeaksUnivariateAllChr}

 \title{Fit a Hidden Markov Model to a ChIP-seq sample.}

 \usage{

-callPeaksUnivariateAllChr(binned.data, control.data = NULL, eps = 0.01,

-  init = "standard", max.time = NULL, max.iter = NULL, num.trials = 1,

-  eps.try = NULL, num.threads = 1, read.cutoff = TRUE,

-  read.cutoff.quantile = 1, read.cutoff.absolute = 500, max.mean = Inf,

-  post.cutoff = 0.5, control = FALSE, keep.posteriors = FALSE,

-  keep.densities = FALSE, verbosity = 1)

+callPeaksUnivariateAllChr(

+  binned.data,

+  control.data = NULL,

+  eps = 0.01,

+  init = "standard",

+  max.time = NULL,

+  max.iter = NULL,

+  num.trials = 1,

+  eps.try = NULL,

+  num.threads = 1,

+  read.cutoff = TRUE,

+  read.cutoff.quantile = 1,

+  read.cutoff.absolute = 500,

+  max.mean = Inf,

+  post.cutoff = 0.5,

+  control = FALSE,

+  keep.posteriors = FALSE,

+  keep.densities = FALSE,

+  verbosity = 1

+)

 }

 \arguments{

 \item{binned.data}{A \code{\link{GRanges-class}} object with binned read counts or a file that contains such an object.}

@@ -4,8 +4,14 @@

 \alias{collapseBins}

 \title{Collapse consecutive bins}

 \usage{

-collapseBins(data, column2collapseBy = NULL, columns2sumUp = NULL,

-  columns2average = NULL, columns2getMax = NULL, columns2drop = NULL)

+collapseBins(

+  data,

+  column2collapseBy = NULL,

+  columns2sumUp = NULL,

+  columns2average = NULL,

+  columns2getMax = NULL,

+  columns2drop = NULL

+)

 }

 \arguments{

 \item{data}{A data.frame containing the genomic coordinates in the first three columns.}

@@ -4,9 +4,16 @@

 \alias{enrichmentAtAnnotation}

 \title{Enrichment of (combinatorial) states for genomic annotations}

 \usage{

-enrichmentAtAnnotation(bins, info, annotation, bp.around.annotation = 10000,

-  region = c("start", "inside", "end"), what = "combinations",

-  num.intervals = 21, statistic = "fold")

+enrichmentAtAnnotation(

+  bins,

+  info,

+  annotation,

+  bp.around.annotation = 10000,

+  region = c("start", "inside", "end"),

+  what = "combinations",

+  num.intervals = 21,

+  statistic = "fold"

+)

 }

 \arguments{

 \item{bins}{The \code{$bins} entry from a \code{\link{multiHMM}} or \code{\link{combinedMultiHMM}} object.}

@@ -7,18 +7,39 @@

 \alias{plotEnrichment}

 \title{Enrichment analysis}

 \usage{

-plotFoldEnrichHeatmap(hmm, annotations, what = "combinations",

-  combinations = NULL, marks = NULL, plot = TRUE, logscale = TRUE)

-

-plotEnrichCountHeatmap(hmm, annotation, bp.around.annotation = 10000,

-  max.rows = 1000, combinations = NULL,

+plotFoldEnrichHeatmap(

+  hmm,

+  annotations,

+  what = "combinations",

+  combinations = NULL,

+  marks = NULL,

+  plot = TRUE,

+  logscale = TRUE

+)

+

+plotEnrichCountHeatmap(

+  hmm,

+  annotation,

+  bp.around.annotation = 10000,

+  max.rows = 1000,

+  combinations = NULL,

   colorByCombinations = sortByCombinations,

-  sortByCombinations = is.null(sortByColumns), sortByColumns = NULL)

-

-plotEnrichment(hmm, annotation, bp.around.annotation = 10000,

-  region = c("start", "inside", "end"), num.intervals = 20,

-  what = "combinations", combinations = NULL, marks = NULL,

-  statistic = "fold", logscale = TRUE)

+  sortByCombinations = is.null(sortByColumns),

+  sortByColumns = NULL

+)

+

+plotEnrichment(

+  hmm,

+  annotation,

+  bp.around.annotation = 10000,

+  region = c("start", "inside", "end"),

+  num.intervals = 20,

+  what = "combinations",

+  combinations = NULL,

+  marks = NULL,

+  statistic = "fold",

+  logscale = TRUE

+)

 }

 \arguments{

 \item{hmm}{A \code{\link{combinedMultiHMM}} or \code{\link{multiHMM}} object or a file that contains such an object.}

@@ -3,7 +3,9 @@

 \name{experiment.table}

 \alias{experiment.table}

 \title{Experiment data table}

-\format{A \code{data.frame} with columns 'file', 'mark', 'condition', 'replicate', 'pairedEndReads' and 'controlFiles'. Avoid the use of special characters like '-' or '+' as this will confuse the internal file management.}

+\format{

+A \code{data.frame} with columns 'file', 'mark', 'condition', 'replicate', 'pairedEndReads' and 'controlFiles'. Avoid the use of special characters like '-' or '+' as this will confuse the internal file management.

+}

 \description{

 A \code{data.frame} specifying the structure of the experiment.

 }

@@ -7,14 +7,31 @@

 \alias{exportCombinations}

 \title{Export genome browser uploadable files}

 \usage{

-exportPeaks(model, filename, header = TRUE, separate.files = TRUE,

-  trackname = NULL)

+exportPeaks(

+  model,

+  filename,

+  header = TRUE,

+  separate.files = TRUE,

+  trackname = NULL

+)

-exportCounts(model, filename, header = TRUE, separate.files = TRUE,

-  trackname = NULL)

+exportCounts(

+  model,

+  filename,

+  header = TRUE,

+  separate.files = TRUE,

+  trackname = NULL

+)

-exportCombinations(model, filename, header = TRUE, separate.files = TRUE,

-  trackname = NULL, exclude.states = "[]", include.states = NULL)

+exportCombinations(

+  model,

+  filename,

+  header = TRUE,

+  separate.files = TRUE,

+  trackname = NULL,

+  exclude.states = "[]",

+  include.states = NULL

+)

 }

 \arguments{

 \item{model}{A \code{\link{chromstaR-objects}}.}

@@ -4,9 +4,17 @@

 \alias{exportGRangesAsBedFile}

 \title{Export genome browser viewable files}

 \usage{

-exportGRangesAsBedFile(gr, trackname, filename, namecol = "combination",

-  scorecol = "score", colorcol = NULL, colors = NULL, header = TRUE,

-  append = FALSE)

+exportGRangesAsBedFile(

+  gr,

+  trackname,

+  filename,

+  namecol = "combination",

+  scorecol = "score",

+  colorcol = NULL,

+  colors = NULL,

+  header = TRUE,

+  append = FALSE

+)

 }

 \arguments{

 \item{gr}{A \code{\link{GRanges-class}} object.}