findOverlappingPeaks: Find the overlapping peaks for two peak ranges.
In ChIPpeakAnno: Batch annotation of the peaks identified from either ChIP-seq, ChIP-chip experiments or any experiments resulted in large number of chromosome ranges

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

Find the overlapping peaks for two input peak ranges.

findOverlappingPeaks(
  Peaks1,
  Peaks2,
  maxgap = -1L,
  minoverlap = 0L,
  multiple = c(TRUE, FALSE),
  NameOfPeaks1 = "TF1",
  NameOfPeaks2 = "TF2",
  select = c("all", "first", "last", "arbitrary"),
  annotate = 0,
  ignore.strand = TRUE,
  connectedPeaks = c("min", "merge"),
  ...
)

`Peaks1`	GRanges: See example below.
`Peaks2`	GRanges: See example below.
`maxgap, minoverlap`	Used in the internal call to `findOverlaps()` to detect overlaps. See `?findOverlaps` in the IRanges package for a description of these arguments.
`multiple`	TRUE or FALSE: TRUE may return multiple overlapping peaks in Peaks2 for one peak in Peaks1; FALSE will return at most one overlapping peaks in Peaks2 for one peak in Peaks1. This parameter is kept for backward compatibility, please use select.
`NameOfPeaks1`	Name of the Peaks1, used for generating column name.
`NameOfPeaks2`	Name of the Peaks2, used for generating column name.
`select`	all may return multiple overlapping peaks, first will return the first overlapping peak, last will return the last overlapping peak and arbitrary will return one of the overlapping peaks.
`annotate`	Include overlapFeature and shortestDistance in the OverlappingPeaks or not. 1 means yes and 0 means no. Default to 0.
`ignore.strand`	When set to TRUE, the strand information is ignored in the overlap calculations.
`connectedPeaks`	If multiple peaks involved in overlapping in several groups, set it to "merge" will count it as only 1, while set it to "min" will count it as the minimal involved peaks in any concered groups
`...`	Objects of GRanges: See also `findOverlapsOfPeaks`.

The new function findOverlapsOfPeaks is recommended.

Efficiently perform overlap queries with an interval tree implemented in IRanges.

OverlappingPeaks

a data frame consists of input peaks information with added information: overlapFeature (upstream: peak1 resides upstream of the peak2; downstream: peak1 resides downstream of the peak2; inside: peak1 resides inside the peak2 entirely; overlapStart: peak1 overlaps with the start of the peak2; overlapEnd: peak1 overlaps with the end of the peak2; includeFeature: peak1 include the peak2 entirely) and shortestDistance (shortest distance between the overlapping peaks)

MergedPeaks

GRanges contains merged overlapping peaks

Lihua Julie Zhu

1.Interval tree algorithm from: Cormen, Thomas H.; Leiserson, Charles E.; Rivest, Ronald L.; Stein, Clifford. Introduction to Algorithms, second edition, MIT Press and McGraw-Hill. ISBN 0-262-53196-8

2.Zhu L.J. et al. (2010) ChIPpeakAnno: a Bioconductor package to annotate ChIP-seq and ChIP-chip data. BMC Bioinformatics 2010, 11:237 doi:10.1186/1471-2105-11-237

3. Zhu L (2013). Integrative analysis of ChIP-chip and ChIP-seq dataset. In Lee T and Luk ACS (eds.), Tilling Arrays, volume 1067, chapter 4, pp. -19. Humana Press. http://dx.doi.org/10.1007/978-1-62703-607-8_8

findOverlapsOfPeaks, annotatePeakInBatch, makeVennDiagram

    if (interactive())
    {    
    peaks1 = 
        GRanges(seqnames=c(6,6,6,6,5), 
                IRanges(start=c(1543200,1557200,1563000,1569800,167889600),
                        end=c(1555199,1560599,1565199,1573799,167893599),
                        names=c("p1","p2","p3","p4","p5")),
                strand=as.integer(1))
    peaks2 = 
        GRanges(seqnames=c(6,6,6,6,5), 
                IRanges(start=c(1549800,1554400,1565000,1569400,167888600),
                        end=c(1550599,1560799,1565399,1571199,167888999),
                        names=c("f1","f2","f3","f4","f5")),
                strand=as.integer(1))
    t1 =findOverlappingPeaks(peaks1, peaks2, maxgap=1000, 
          NameOfPeaks1="TF1", NameOfPeaks2="TF2", select="all", annotate=1) 
    r = t1$OverlappingPeaks
    pie(table(r$overlapFeature))
    as.data.frame(t1$MergedPeaks)
    }