windowCounts {ChIPseqR} | R Documentation

## Summarize read counts in a sliding window

### Description

Read counts are summarized in a sliding window of variable size with variable overlap between windows.

### Usage

    windowCounts(reads, window = 1000, shift = 500, method = sum)

### Arguments

`reads` | Numeric vector of read counts.
`window` | Width of window.
`shift` | Distance between consecutive window start positions.
`method` | Function used to produce a summary for each window. It should accept a single numeric vector as argument.

### Value

If `method` returns a single value a vector of all window summaries is returned, otherwise the return value is a list with one component for each window.

### Author(s)

Peter Humburg

### Examples

    ## generate some very simple artificial read data
    set.seed(1)
    fwd <- sample(c(50:70, 250:270), 30, replace=TRUE)
    rev <- sample(c(197:217, 347:417), 30, replace=TRUE)
    ## create data.frame with read positions as input to strandPileup
    reads <- data.frame(chromosome="chr1", position=c(fwd, rev),
    	length=25, strand=factor(rep(c("+", "-"), times=c(30, 30))))

    ## create object of class ReadCounts
    readPile <- strandPileup(reads, chrLen=501, extend=1, plot=FALSE, compress=FALSE)

    ## get number of reads in sliding window
    wdwCount <- windowCounts(apply(readPile[[1]], 1, sum), window=10, shift=5)

[Package ChIPseqR version 1.40.0 Index]