cherByThreshold: Function to identify chers based on thresholds
In Ringo: R Investigation of ChIP-chip Oligoarrays

Description Usage Arguments Details Value Author(s) See Also Examples

Given a vector of probe positions on the chromosome, a vector of smoothed intensities on these positions, and a threshold for intensities to indicated enrichment, this function identifies Chers (ChIP-enriched regions) on this chromosome.

This function is called by the function findChersOnSmoothed.

1 2	cherByThreshold(positions, scores, threshold, distCutOff, minProbesInRow = 3)

`positions`	numeric vector of genomic positions of probes
`scores`	scores (intensities) of probes on those positions
`threshold`	threshold for scores to be called a cher
`distCutOff`	maximal positional distance between two probes to be part of the same cher
`minProbesInRow`	integer; minimum number of enriched probes required for a cher; see `details` for further explanation.

Specifying a minimum number of probes for a cher (argument minProbesInRow) guarantees that a cher is supported by a reasonable number of measurements in probe-sparse regions. For example, if there's only one enriched probe within a certain genomic 1kb region and no other probes can been mapped to that region, this single probe does arguably not provide enough evidence for calling this genomic region enriched.

A LIST with n components, where the first n components are the cher clusters, each one holding the scores and, as their names, the genomic positions of probes in that cluster.

Joern Toedling

findChersOnSmoothed

 ## example with random generated data:
 rpos <- cumsum(round(runif(200)*5))
 rsco <- rnorm(200)+0.2
 plot(rpos, rsco, type="l", col="seagreen3", lwd=2)
 rug(rpos, side=1, lwd=2); abline(h=0, lty=2)              
 rchers <- cherByThreshold(rpos, rsco, threshold=0, distCutOff=2)
 sapply(rchers[-length(rchers)], function(thisClust){
  points(x=as.numeric(names(thisClust)), y=thisClust, type="h", lwd=2,
 col="gold")})