plotPatterns | R Documentation |
'plotPatterns()' plots the posterior probabilities associated with differential patterns from a differential analysis of 'epigraHMM()'
plotPatterns(
object,
ranges,
peaks,
hdf5 = metadata(object)$output,
colors = NULL
)
object |
an epigraHMMDataSet |
ranges |
a GRanges object or a pair of integers with the genomic corrdinates/windows to be plotted |
peaks |
either a GRanges object or a vector of logicals (with length equal to the number of rows in 'object') specifying the genomic corrdinates/windows with peaks |
hdf5 |
a character string with the hdf5 file path from 'epigraHMM' |
colors |
an optional argument that specifies the colors for each differential combinatorial pattern |
A pheatmat
Pedro L. Baldoni, pedrobaldoni@gmail.com
https://github.com/plbaldoni/epigraHMM
# Creating dummy object
countData <- cbind(rbind(matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1),
matrix(rnbinom(1e2, mu = 10, size = 5), ncol = 1),
matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1),
matrix(rnbinom(1e2, mu = 10, size = 5), ncol = 1),
matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1),
matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1),
matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1)),
rbind(matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1),
matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1),
matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1),
matrix(rnbinom(1e2, mu = 10, size = 5), ncol = 1),
matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1),
matrix(rnbinom(1e2, mu = 10, size = 5), ncol = 1),
matrix(rnbinom(1e2, mu = 1, size = 10), ncol = 1)))
colData <- data.frame(condition = c('A','B'), replicate = c(1,1))
rowRanges <- GenomicRanges::GRanges('chrA',
IRanges::IRanges(start = seq(1,by = 500,
length.out = nrow(countData)),width = 500))
object <- epigraHMMDataSetFromMatrix(countData,colData,rowRanges = rowRanges)
# Initializing
object <- initializer(object,controlEM())
# Running epigraHMM
object <- epigraHMM(object,controlEM(),type = 'differential',dist = 'nb')
# Calling peaks
peaks <- callPeaks(object = object,
hdf5 = S4Vectors::metadata(object)$output,
method = 'viterbi')
# Plotting patterns
plotPatterns(object,
ranges = peaks[1],
peaks = peaks)
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