Combinatorial and Differential Chromatin State Analysis for ChIP-Seq Data

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Documentation for package ‘chromstaR’ version 1.30.0

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chromstaR-package Combinatorial and differential chromatin state analysis for ChIP-seq data
bin2dec Conversion of decimal and binary states
binned.data Binned read counts
binning Convert aligned reads from various file formats into read counts in equidistant bins
binReads Convert aligned reads from various file formats into read counts in equidistant bins
callPeaksMultivariate Fit a Hidden Markov Model to multiple ChIP-seq samples
callPeaksReplicates Fit a multivariate Hidden Markov Model to multiple ChIP-seq replicates
callPeaksUnivariate Fit a Hidden Markov Model to a ChIP-seq sample.
callPeaksUnivariateAllChr Fit a Hidden Markov Model to a ChIP-seq sample.
changeFDR Adjust sensitivity of peak detection
changeMaxPostCutoff Adjust sensitivity of peak detection
changePostCutoff Change the posterior cutoff of a Hidden Markov Model
Chromstar Wrapper function for the 'chromstaR' package
chromstaR Combinatorial and differential chromatin state analysis for ChIP-seq data
chromstaR-objects chromstaR objects
collapseBins Collapse consecutive bins
combinatorialStates Get the (decimal) combinatorial states of a list of univariate HMM models
combinedHMM Combined multivariate HMM object
combinedMultiHMM Combined multivariate HMM object
combineMultivariates Combine combinatorial states from several Multivariates
conversion Conversion of decimal and binary states
dec2bin Conversion of decimal and binary states
differentialScoreMax chromstaR scores
differentialScoreSum chromstaR scores
dzinbinom The Zero-inflated Negative Binomial Distribution
enrichmentAtAnnotation Enrichment of (combinatorial) states for genomic annotations
enrichment_analysis Enrichment analysis
experiment.table Experiment data table
exportCombinations Export genome browser uploadable files
exportCounts Export genome browser uploadable files
exportFiles Export genome browser uploadable files
exportGRangesAsBedFile Export genome browser viewable files
exportPeaks Export genome browser uploadable files
fixedWidthBins Make fixed-width bins
genes_rn4 Gene coordinates for rn4
genomicFrequencies Frequencies of combinatorial states
getCombinations Get combinations
getDistinctColors Get distinct colors
getStateColors Get state colors
heatmapCombinations Plot a heatmap of combinatorial states
heatmapCountCorrelation Read count correlation heatmap
heatmapTransitionProbs Heatmap of transition probabilities
loadHmmsFromFiles Load 'chromstaR' objects from file
mergeChroms Merge several 'multiHMM's into one object
model.combined Combined multivariate HMM for demonstration purposes
model.multivariate Multivariate HMM for demonstration purposes
model.univariate Univariate HMM for demonstration purposes
multi.hmm Multivariate HMM object
multiHMM Multivariate HMM object
multivariateSegmentation Multivariate segmentation
plotEnrichCountHeatmap Enrichment analysis
plotEnrichment Enrichment analysis
plotExpression Overlap with expression data
plotFoldEnrichHeatmap Enrichment analysis
plotGenomeBrowser #' Plot a genome browser view #' #' Plot a simple genome browser view. This is useful for scripted genome browser snapshots. #' #' @param counts A 'GRanges-class' object with meta-data column 'counts'. #' @param peaklist A named list() of 'GRanges-class' objects containing peak coordinates. #' @param chr,start,end Chromosome, start and end coordinates for the plot. #' @param countcol A character giving the color for the counts. #' @param peakcols A character vector with colors for the peaks in 'peaklist'. #' @param style One of 'c('peaks', 'density')'. #' @param peakTrackHeight Relative height of the tracks given in 'peaklist' compared to the 'counts'. #' @return A 'ggplot' object. #' @examples #'## Get an example multiHMM ## #'file <- system.file("data","multivariate_mode-combinatorial_condition-SHR.RData", #' package="chromstaR") #'model <- get(load(file)) #'## Plot genome browser snapshot #'bins <- model$bins #'bins$counts <- model$bins$counts.rpkm[,1] #'plotGenomeBrowser(counts=bins, peaklist=model$peaks, #' chr='chr12', start=1, end=1e6) #' plotGenomeBrowser2 <- function(counts, peaklist=NULL, chr, start, end, countcol='black', peakcols=NULL, style='peaks', peakTrackHeight=5) ## Select ranges to plot ranges2plot <- reduce(counts[counts@seqnames == chr & start(counts) >= start & start(counts) <= end]) ## Counts counts <- subsetByOverlaps(counts, ranges2plot) if (style == 'peaks') df <- data.frame(x=(start(counts)+end(counts))/2, counts=counts$counts) # plot triangles centered at middle of the bin ggplt <- ggplot(df) + geom_area(aes_string(x='x', y='counts')) + theme(panel.grid = element_blank(), panel.background = element_blank(), axis.text.x = element_blank(), axis.title = element_blank(), axis.ticks.x = element_blank(), axis.line = element_blank()) maxcounts <- max(counts$counts) ggplt <- ggplt + scale_y_continuous(breaks=c(0, maxcounts)) else if (style == 'density') df <- data.frame(xmin=start(counts), xmax=end(counts), counts=counts$counts) ggplt <- ggplot(df) + geom_rect(aes_string(xmin='xmin', xmax='xmax', ymin=0, ymax=4, alpha='counts')) + theme(panel.grid = element_blank(), panel.background = element_blank(), axis.text = element_blank(), axis.title = element_blank(), axis.ticks = element_blank(), axis.line = element_blank()) else stop("Unknown value '", style, "' for parameter 'style'. Must be one of c('peaks', 'density').") ## Peaks if (!is.null(peaklist)) if (is.null(peakcols)) peakcols <- getDistinctColors(length(peaklist)) for (i1 in 1:length(peaklist)) p <- peakTrackHeight peaks <- subsetByOverlaps(peaklist[[i1]], ranges2plot) if (length(peaks) > 0) df <- data.frame(start=start(peaks), end=end(peaks), ymin=-p*i1, ymax=-p*i1+0.9*p) ggplt <- ggplt + geom_rect(data=df, mapping=aes_string(xmin='start', xmax='end', ymin='ymin', ymax='ymax'), col=peakcols[i1], fill=peakcols[i1]) trackname <- names(peaklist)[i1] df <- data.frame(x=start(counts)[1], y=-p*i1+0.5*p, label=trackname) ggplt <- ggplt + geom_text(data=df, mapping=aes_string(x='x', y='y', label='label'), vjust=0.5, hjust=0.5, col=peakcols[i1]) return(ggplt) Plot a genome browser view
plotHistogram Histogram of binned read counts with fitted mixture distribution
plotHistograms Histograms of binned read counts with fitted mixture distribution
plotting chromstaR plotting functions
print.combinedMultiHMM Print combinedMultiHMM object
print.multiHMM Print multiHMM object
print.uniHMM Print uniHMM object
pzinbinom The Zero-inflated Negative Binomial Distribution
qzinbinom The Zero-inflated Negative Binomial Distribution
readBamFileAsGRanges Import BAM file into GRanges
readBedFileAsGRanges Import BED file into GRanges
readConfig Read chromstaR configuration file
readCustomBedFile Read bed-file into GRanges
removeCondition Remove condition from model
rzinbinom The Zero-inflated Negative Binomial Distribution
scanBinsizes Find the best bin size for a given dataset
scores chromstaR scores
simulateMultivariate Simulate multivariate data
simulateReadsFromCounts Simulate read coordinates
simulateUnivariate Simulate univariate data
state.brewer Obtain combinatorial states from specification
stateBrewer Obtain combinatorial states from experiment table
subsample Normalize read counts
transitionFrequencies Transition frequencies of combinatorial states
uni.hmm Univariate HMM object
uniHMM Univariate HMM object
unis2pseudomulti Combine univariate HMMs to a multivariate HMM
variableWidthBins Make variable-width bins
writeConfig Write chromstaR configuration file
zinbinom The Zero-inflated Negative Binomial Distribution