@@ -115,6 +115,8 @@ heatmapCountCorrelation <- function(model, cluster=TRUE) {

 #' Plot a heatmap of transition probabilities for a \code{\link{multiHMM}} model.

 #'

 #' @param model A \code{\link{multiHMM}} object or file that contains such an object.

+#' @param reorder.states Whether or not to reorder the states.

+#' @param transitionProbs A matrix with transition probabilities where \code{dimnames(emissionProbs)} gives the state labels. This option is helpful to plot transition probabilities directly without needing a \code{\link{chromstaR-objects}}. If specified, \code{model} will be ignored.

 #' @return A \code{\link[ggplot2]{ggplot}} object.

 #' @importFrom reshape2 melt

 #' @seealso \code{\link{plotting}}

@@ -125,14 +127,31 @@ heatmapCountCorrelation <- function(model, cluster=TRUE) {

 #'                     package="chromstaR")

 #'model <- get(load(file))

 #'## Plot transition probabilites as heatmap

-#'heatmapTransitionProbs(model)

+#'heatmapTransitionProbs(model, reorder.states=TRUE)

 #'

-heatmapTransitionProbs <- function(model) {

-

-    model <- suppressMessages( loadHmmsFromFiles(model, check.class=class.multivariate.hmm)[[1]] )

-    A <- reshape2::melt(model$transitionProbs, varnames=c('from','to'), value.name='prob')

-    A$from <- factor(A$from, levels=stateorderByTransition(model))

-    A$to <- factor(A$to, levels=stateorderByTransition(model))

+heatmapTransitionProbs <- function(model=NULL, reorder.states=TRUE, transitionProbs=NULL) {

+

+    if (is.null(transitionProbs)) {

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

+        transitionProbs <- model$transitionProbs

+        A <- reshape2::melt(transitionProbs, varnames=c('from','to'), value.name='prob')

+        if (reorder.states) {

+            A$from <- factor(A$from, levels=stateorderByTransition(transitionProbs))

+            A$to <- factor(A$to, levels=stateorderByTransition(transitionProbs))

+        } else {

+            A$from <- factor(A$from, levels=levels(model$bins$combination))

+            A$to <- factor(A$to, levels=levels(model$bins$combination))

+        }

+    } else {

+        A <- reshape2::melt(transitionProbs, varnames=c('from','to'), value.name='prob')

+        if (reorder.states) {

+            A$from <- factor(A$from, levels=stateorderByTransition(transitionProbs))

+            A$to <- factor(A$to, levels=stateorderByTransition(transitionProbs))

+        } else {

+            A$from <- factor(A$from, levels=colnames(transitionProbs))

+            A$to <- factor(A$to, levels=colnames(transitionProbs))

+        }

+    }

     ggplt <- ggplot(data=A) + geom_tile(aes_string(x='to', y='from', fill='prob')) + theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust=0.5)) + scale_fill_gradient(low="white", high="blue")

     return(ggplt)

@@ -1,20 +1,18 @@

-stateorderByTransition <- function(multi.hmm) {

-

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

+stateorderByTransition <- function(transitionProbs) {

     ## Calculate distance matrix

-    distances <- matrix(NA, ncol=ncol(multi.hmm$transitionProbs), nrow=nrow(multi.hmm$transitionProbs))

-    colnames(distances) <- colnames(multi.hmm$transitionProbs)

-    rownames(distances) <- rownames(multi.hmm$transitionProbs)

+    distances <- matrix(NA, ncol=ncol(transitionProbs), nrow=nrow(transitionProbs))

+    colnames(distances) <- colnames(transitionProbs)

+    rownames(distances) <- rownames(transitionProbs)

     for (irow in 1:nrow(distances)) {

         for (icol in 1:ncol(distances)) {

-            distances[irow,icol] <- 2 - (multi.hmm$transitionProbs[irow,icol] + multi.hmm$transitionProbs[icol,irow])

-#             distances[irow,icol] <- abs(multi.hmm$transitionProbs[irow,icol] - multi.hmm$transitionProbs[icol,irow])

+            distances[irow,icol] <- 2 - (transitionProbs[irow,icol] + transitionProbs[icol,irow])

+#             distances[irow,icol] <- abs(transitionProbs[irow,icol] - transitionProbs[icol,irow])

         }

     }

     ## Select ordering

-    comb.states <- colnames(multi.hmm$transitionProbs)

+    comb.states <- colnames(transitionProbs)

     stateorders <- matrix(NA, ncol=length(comb.states), nrow=length(comb.states))

     total.distance <- rep(0, length(comb.states))

     for (i1 in 1:length(comb.states)) {

@@ -30,8 +28,6 @@ stateorderByTransition <- function(multi.hmm) {

         }

     }

     stateorder <- stateorders[which.min(total.distance),]

-

-    ## Reorder the multi.hmm

     return(stateorder)

 }

@@ -4,10 +4,15 @@

 \alias{heatmapTransitionProbs}

 \title{Heatmap of transition probabilities}

 \usage{

-heatmapTransitionProbs(model)

+heatmapTransitionProbs(model = NULL, reorder.states = TRUE,

+  transitionProbs = NULL)

 }

 \arguments{

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

+

+\item{reorder.states}{Whether or not to reorder the states.}

+

+\item{transitionProbs}{A matrix with transition probabilities where \code{dimnames(emissionProbs)} gives the state labels. This option is helpful to plot transition probabilities directly without needing a \code{\link{chromstaR-objects}}. If specified, \code{model} will be ignored.}

 }

 \value{

 A \code{\link[ggplot2]{ggplot}} object.

@@ -21,7 +26,7 @@ file <- system.file("data","multivariate_mode-combinatorial_condition-SHR.RData"

                     package="chromstaR")

 model <- get(load(file))

 ## Plot transition probabilites as heatmap

-heatmapTransitionProbs(model)

+heatmapTransitionProbs(model, reorder.states=TRUE)

 }

 \seealso{

new file mode 100644

@@ -0,0 +1,70 @@

+% Generated by roxygen2: do not edit by hand

+% Please edit documentation in R/importOtherSegmentations.R

+\name{importChromHMMsegmentation}

+\alias{importChromHMMsegmentation}

+\title{Import ChromHMM segmentation}

+\usage{

+importChromHMMsegmentation(inputfolder, outputfolder, assembly, binsize,

+  experiment.table, chrom.lengths = NULL, chromosomes = NULL,

+  chromosome.format = "UCSC")

+}

+\arguments{

+\item{inputfolder}{Folder with ChromHMM output files (segmentation, emission and transition probabilities).}

+

+\item{outputfolder}{Output folder for the converted \code{\link{chromstaR-objects}}.}

+

+\item{assembly}{An assembly from which the chromosome lengths are determined. Please see \code{\link[GenomeInfoDb]{fetchExtendedChromInfoFromUCSC}} for available assemblies. Alternatively a data.frame generated by \code{\link[GenomeInfoDb]{fetchExtendedChromInfoFromUCSC}}.}

+

+\item{binsize}{The bin size in base pairs used in ChromHMM.}

+

+\item{experiment.table}{A \code{data.frame} or tab-separated text file with the structure of the experiment. See \code{\link{experiment.table}} for an example.}

+

+\item{chrom.lengths}{A named character vector with chromosome lengths. Names correspond to chromosomes.}

+

+\item{chromosomes}{A subset of chromosomes for which the bins are generated.}

+

+\item{chromosome.format}{A character specifying the format of the chromosomes if \code{assembly} is specified. Either 'NCBI' for (1,2,3 ...) or 'UCSC' for (chr1,chr2,chr3 ...).}

+}

+\value{

+A \code{\link{combinedMultiHMM}} object. Intermediate \code{\link{multiHMM}} objects are saved to \code{outputfolder}.

+}

+\description{

+Import a chromatin state segmentation produced by ChromHMM as \code{\link{chromstaR-objects}}. This is useful to perform comparative analyses or simply use chromstaR plotting or enrichment functions on a ChromHMM segmentation.

+}

+\details{

+The function takes the *segments.bed files, emissions_*.txt and transitions_*.txt files in \code{inputfolder}, and converts them into \code{\link{multiHMM}} objects for each condition that was specified in the \code{experiment.table}. All \code{\link{multiHMM}} objects are then combined into a \code{\link{combinedMultiHMM}} object and returned.

+}

+\examples{

+inputfolder <- "differential_CD4_numstates_16_binsize_1000bp"

+outputfolder <- "testconvertChromHMM2chromstar"

+assembly <- "mm9"

+binsize <- 1000

+chrom.lengths <- NULL

+chromosomes <- paste0("chr", c(1:19, "X"))

+chromosome.format <- "UCSC"

+experiment.table <- "differential_CD4_numstates_16_binsize_1000bp/experiment_table_differential_CD4.tsv"

+model <- importChromHMMsegmentation(inputfolder, outputfolder, assembly, binsize, experiment.table, chrom.lengths, chromosomes, chromosome.format)

+

+### Plot transition and emission probabilities of ChromHMM model ###

+heatmapTransitionProbs(reorder.states=FALSE, transitionProbs=model$transitionProbs)

+heatmapCombinations(emissionProbs = model$emissionProbs)

+

+### Use plotEnrichment function on imported ChromHMM segmentation ###

+library(biomaRt)

+ensembl <- useMart('ENSEMBL_MART_ENSEMBL', host='may2012.archive.ensembl.org',

+                  dataset='mmusculus_gene_ensembl')

+genes <- getBM(attributes=c('ensembl_gene_id', 'chromosome_name', 'start_position',

+                           'end_position', 'strand', 'external_gene_id',

+                           'gene_biotype'),

+              mart=ensembl)

+# Transform to GRanges for easier handling

+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)

+print(genes)

+

+ggplts <- plotEnrichment(model, annotation=genes)

+ggplts[[1]] + facet_wrap(~combination)

+

+}