plotPatterns {epigraHMM} | R Documentation

## Create a plot of differerential patterns posterior probabilities from epigraHMM

### Description

'plotPatterns()' plots the posterior probabilities associated with differential patterns from a differential analysis of 'epigraHMM()'

### Usage

    plotPatterns(
      object,
      ranges,
      peaks,
      hdf5 = metadata(object)$output,
      colors = NULL
    )

### Arguments

`object` | an epigraHMMDataSet
`ranges` | a GRanges object or a pair of integers with the genomic corrdinates/windows to be plotted
`peaks` | either a GRanges object or a vector of logicals (with length equal to the number of rows in 'object') specifying the genomic corrdinates/windows with peaks
`hdf5` | a character string with the hdf5 file path from 'epigraHMM'
`colors` | an optional argument that specifies the colors for each differential combinatorial pattern

### Value

A pheatmat

### Author(s)

Pedro L. Baldoni, pedrobaldoni@gmail.com

### References

https://github.com/plbaldoni/epigraHMM

### Examples

    # Creating dummy object
    countData <- cbind(rbind(matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1),
                             matrix(rnbinom(1e2, mu = 10, size = 5), ncol = 1),
                             matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1),
                             matrix(rnbinom(1e2, mu = 10, size = 5), ncol = 1),
                             matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1),
                             matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1),
                             matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1)),
                       rbind(matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1),
                             matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1),
                             matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1),
                             matrix(rnbinom(1e2, mu = 10, size = 5), ncol = 1),
                             matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1),
                             matrix(rnbinom(1e2, mu = 10, size = 5), ncol = 1),
                             matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1)))

    colData <- data.frame(condition = c('A','B'), replicate = c(1,1))
    rowRanges <- GenomicRanges::GRanges('chrA',
                         IRanges::IRanges(start = seq(1,by = 500,
                         length.out = nrow(countData)),width = 500))

    object <- epigraHMMDataSetFromMatrix(countData,colData,rowRanges = rowRanges)

    # Initializing
    object <- initializer(object,controlEM())

    # Running epigraHMM
    object <- epigraHMM(object,controlEM(),type = 'differential',dist = 'nb')

    # Calling peaks
    peaks <- callPeaks(object = object,
                      hdf5 = S4Vectors::metadata(object)$output,
                      method = 'viterbi')

    # Plotting patterns
    plotPatterns(object,
                 ranges = peaks[1],
                 peaks = peaks)

[Package epigraHMM version 1.0.8 Index]