sliding.median {Ringo}R Documentation

Compute median score over a running window

Description

Compute median score over a sliding window.

Usage

sliding.median(positions, scores, half.width, return.counts = TRUE)

Arguments

positions numeric; sorted vector of (genomic) positions of scores
scores numeric; scores to be smoothed associated to the positions
half.width numeric, half the window size of the sliding window
return.counts logical; should the number of points, e.g. probes, that were used for computing the median in each sliding window also returned?

Details

For each position of argument positions, the median score over a window of size 2*half.width is computed as a smoothed score. For the smoothed score at position i, scores at adjacent positions j are included in the median computation as long as they are not further than half.width away from positions[i].

Value

Matrix with two columns:

median medians over running window centered at the positions that were specified in argument positions.
count number of points that were considerd for computing the median at each position

These positions are given as row.names of the resulting vector.
If argument return.counts is FALSE, only a vector of the medians is returned, with the positions as names.

Author(s)

Oleg Sklyar and Joern Toedling

See Also

median,sliding.quantile

Examples

  sampleSize <- 1000
  ap <- cumsum(1+round(runif(sampleSize)*10))
  as <- c(rnorm(floor(sampleSize/3)),
          rnorm(ceiling(sampleSize/3),mean=1.5),
          rnorm(floor(sampleSize/3)))
  arm <- sliding.median(ap, as, 20)
  plot(ap, as, pch=20, xlab="position",ylab="level")
  points(ap, arm[,1], type="l", col="red", lwd=2)

[Package Ringo version 1.0.0 Index]