sliding.quantile {Ringo} | R Documentation

## Compute quantile of scores in a sliding window

### Description

This functions is used to slide a window of specified size over scores at given positions. Computed is the quantile over the scores in the window.

### Usage

    sliding.quantile(positions, scores, half.width, prob = 0.5,
                     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
`prob` | numeric specifying which quantile is to be computed over the scores in the window; default 0.5 means compute the median over the scores.
`return.counts` | logical; should the number of points, e.g. probes, that were used for computing the median in each sliding window also returned?

### Value

Matrix with two columns:

`quantile` | medians over running window centered at the positions that were specified in argument `positions`.
`count` | number of points that were considered 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

`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.quantile(ap, as, 20)
      arq <- sliding.quantile(ap, as, 20, prob=0.25)
      plot(ap, as, pch=20, xlab="position",ylab="level")
      points(ap, arm[,1], type="l", col="red", lwd=2)
      points(ap, arq[,1], type="l", col="green", lwd=2)
      legend(x="topleft", legend=c("median","1st quartile"),
             col=c("red","green"), lty=1, lwd=2)

[Package Ringo version 1.42.1 Index]