summarise.peaks: Summarize Peaks
In BayesPeak: Bayesian Analysis of ChIP-seq Data

Description Usage Arguments Value Author(s) See Also Examples

View source: R/bayespeak.R

Summarize Peaks - Combine the potentially enriched bins found by BayesPeak into contiguous peaks, and associate each with a posterior probability. summarise.peaks is an alias for summarize.peaks

1 2	summarize.peaks(x, threshold = 0.5, method = c("lowerbound", "max"), exclude.jobs = NULL) summarise.peaks(x, threshold = 0.5, method = c("lowerbound", "max"), exclude.jobs = NULL)

`x`	Raw output from the function `bayespeak`.
`threshold`	Numeric vector. `threshold` must have length equal to either 1 or `nrow(x$QC)` (i.e. the number of jobs). If `threshold` is of length 1, then for each job, all bins with a posterior probability (PP) lower than `threshold` will be discarded before summarising. If `threshold` is of length `nrow(x$QC)`, then jobs are taken to have separate thresholds - in other words, bins in job i will be discarded if they have a PP less than threshold[i]. Note that this behaviour is irrespective of how many jobs are excluded (see the exclude.jobs argument below) - excluded jobs are still assigned a PP threshold, which is essentially ignored.
`method`	The method used to combine the posterior probabilities of multiple peaks. Current methods are: `lowerbound`: A lower bound is found for the posterior probability of the region containing a peak. In contiguous regions of moderately high probability, this method should report a fairer value than `method = max`. Suppose we have a set of n non-intersecting calls within our region, with posterior probabilities p_1 to p_n respectively of containing peaks. Then the probability of there being a peak in this region is at least 1 - (1-p_1)...(1-p_n). We maximise this over all possible sets of non-intersecting calls within the region. (Usually, this will simply be a choice between exclusively using the offset or the non-offset analyses.) `max`: Combined region has probability equal to the maximum posterior probability over all the peaks it contains.
`exclude.jobs`	A vector of integers, denoting jobs to be excluded from later analysis. Alternatively, a logical vector (to be passed through `which()`).

A RangedData object corresponding to the peaks called - each range has an associated PP (Posterior Probability) value.

Jonathan Cairns

bayespeak.

dir <- system.file("extdata", package="BayesPeak")
treatment <- file.path(dir, "H3K4me3reduced.bed")
input <- file.path(dir, "Inputreduced.bed")

##look at specific region 92-95Mb on chromosome 16
##(we've used half the number of iterations here to reduce the time this example takes)
raw.output <- bayespeak(treatment, input, chr = "chr16", start = 9.2E7, end = 9.5E7, iterations = 5000L, use.multicore = TRUE)
output <- summarize.peaks(raw.output)
output

##higher threshold
output.ht <- summarize.peaks(raw.output, threshold = 0.9)
output.ht