This function leverages a Markov model in order to determine the clump start probability. The computation depends on the selected false positive probability for calling motif matches 'alpha' and the pre-determined overlapping match probabilities 'beta'.
An Overlap object.
The general idea of the method relies on the fact that for the stationary distribution of the Markov model, motif matches must be observed with probability 'alpha'. Hence, the clump start probability 'tau' is optimized to achieve that goal.
The R interface is only used for the purpose of testing the correctness of the model.
Clump start probability 'tau'
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# Load sequences seqfile = system.file("extdata", "seq.fasta", package = "motifcounter") seqs = Biostrings::readDNAStringSet(seqfile) # Load motif motiffile = system.file("extdata", "x31.tab", package = "motifcounter") motif = t(as.matrix(read.table(motiffile))) # Load background model bg = readBackground(seqs, 1) # Compute overlap probabilities op = motifcounter:::probOverlapHit(motif, bg, singlestranded = FALSE) # Computes the clump start probability dist = motifcounter:::computeClumpStartProb(op)
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