Nothing

```
#' Combinatrial model approximation of the number of motif hits
#'
#' This function approxmiates the distribution of the number of motif hits.
#' To this end, it sums over all combinations of obtaining k hits
#' in a random sequence of a given length using an efficient
#' dynamic programming algorithm.
#'
#' This function is an alternative to \code{\link{compoundPoissonDist}}
#' which requires fixed-length sequences and currently
#' only supports the computation of
#' the distribution of the number of hits when both
#' DNA strands are scanned for motif hits.
#'
#' @include comppoiss_wrapper.R
#'
#' @inheritParams compoundPoissonDist
#'
#' @return List containing
#' \describe{
#' \item{dist}{Distribution of the number of hits}
#' }
#' @seealso \code{\link{compoundPoissonDist}}
#' @seealso \code{\link{numMotifHits}}
#' @seealso \code{\link{probOverlapHit}}
#' @examples
#'
#' # 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)
#'
#' # Use 2 sequences of length 100 bp each
#' seqlen = rep(100, 2)
#'
#' # Computes the combinatorial distribution of the number of motif hits
#' dist = motifcounter:::combinatorialDist(seqlen, op)
#'
combinatorialDist = function(seqlen, overlap) {
stopifnot(is(overlap, "Overlap"))
# Length must be at least as long as the motif
if (seqlen[1] - length(getBeta(overlap)) + 1 <= 0) {
return (list(dist = 1))
}
# The remaining sequence must be of equal length!
if (!all(seqlen == seqlen[1])) {
stop("All elements in 'seqlen' must be equal.")
}
if (getSinglestranded(overlap) == TRUE) {
# This might change in the future though
stop(
paste(strwrap("The combinatorial model can only be used
with 'singlestranded = FALSE' (see probOverlapHit)."),
collapse = "\n")
)
}
# Analysing too short sequences might result in biases
# of the model
if (seqlen[1] < 30) {
warning(paste(strwrap(
"seqlen[1] < 30 bp: Short sequences might incur
biases in the analysis.
If possible, use longer sequences (e.g. seqlen[1] >= 100)."),
collapse="\n")
)
}
# the maximal number of hits is given by the sequence length
maxhits = seqlen[1]
# allocate the distribution of the number of hits
# across multiple sequences
totalmaxhits = maxhits * length(seqlen)
dist = numeric(totalmaxhits + 1)
ret = .C(
motifcounter_combinatorialDist,
getAlpha(overlap),
getBeta(overlap),
getBeta3p(overlap),
getBeta5p(overlap),
as.numeric(dist),
as.integer(seqlen[1]),
as.integer(maxhits),
as.integer(length(seqlen)),
length(getBeta(overlap)),
as.integer(getSinglestranded(overlap))
)
if (is.na(sum(ret[[5]]))) {
# This might be the case if too stringent
# and too long or too many sequences shall be
# assessed for significant enrichment.
# In this case, the combinatorial model is pushed
# to its limits
stop(
paste(strwrap("Numerical issue detected.
Please try to reduce the number (see 'length(seqlen)') and/or
length of sequences (see 'seqlen[1]'). Alternatively,
please try to use the 'compound Poisson approximation'
instead of the 'combinatorial approximation'."),
collapse = "\n")
)
}
return(list(dist = ret[[5]]))
}
```

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