Get the combinatorial states of a list of models generated by callPeaksUnivariate
. The function returns the decimal combinatorial states for each bin (see details for an explanation of combinatorial state).
1  combinatorialStates(hmm.list, binary = FALSE)

hmm.list 
A list of models generated by 
binary 
If 
For a given model, each genomic bin can be either called 'unmodified' or 'modified', depending on the posterior probabilities estimated by the BaumWelch. Thus, a list of models defines a binary combinatorial state for each bin. This binary combinatorial state can be expressed as a decimal number. Example: We have 4 histone modifications, and we run the univariate HMM for each of them. Then we use a false discovery rate of 0.5 to call each bin either 'unmodified' or 'modified'. The resulting binary combinatorial states can then be converted to decimal representation. The following table illustrates this:
bin  modification state  decimal state  
model1  model2  model3  model4  
1  0  0  1  0  2 
2  0  0  0  0  0 
3  0  1  1  0  6 
4  0  1  1  1  7 
Output is a vector of integers representing the combinatorial state of each bin.
Aaron Taudt
dec2bin
, bin2dec
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19  # Get example BAM files for 3 different marks in hypertensive rat (SHR)
file.path < system.file("extdata","euratrans", package='chromstaRData')
files < list.files(file.path, full.names=TRUE, pattern='SHR.*bam$')[c(1,4,6)]
# Bin the data
data(rn4_chrominfo)
binned.data < list()
for (file in files) {
binned.data[[basename(file)]] < binReads(file, binsizes=1000,
assembly=rn4_chrominfo, chromosomes='chr12')
}
# Obtain the univariate fits
models < list()
for (i1 in 1:length(binned.data)) {
models[[i1]] < callPeaksUnivariate(binned.data[[i1]], max.time=60, eps=1)
}
## Get the decimal representation of the combinatorial state of this combination of models
states < chromstaR:::combinatorialStates(models, binary=FALSE)
## Show number of each state
table(states)

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