segN {aCGH.Spline}R Documentation

Segmentation method.

Description

Java method that performs segmentation using a 'RandomWalk' algorithm.

Usage

segN(ddd)

Arguments

ddd - vector of ratio values (sorted by genomic postion).

Details

This method segments and assesses the difference between consecutive data points using a 'RandomWalk' approach.

Value

A vector of length (ddd) containing the segment medians.

Note

This method is static and has no paramethers available for the user.
NB. The full method will be available as an R package soon.

Author(s)

Tomas William Fitzgerald

Examples


v = seq(1,100000,0.5)
d = sin(2*pi/500 * v) 
red = d  +  rnorm(length(d),0,100) + 1000
dd = sin(2*pi/1000 * v) 
green = dd  +  rnorm(length(dd),0,120) + 1000
 rat = log2(red / green) - median(log2(red / green), na.rm=TRUE)
 rat[20000:30000] = abs(rat[20000:30000] * 2)
 rat[60000:70000] = -abs(rat[60000:70000] * 2)
 seg  = segN(rat)
 par(mfrow=c(2,1))
 plot(rat, pch=46, ylim=c(-2,2), main="Before_segN")
 plot(rat, pch=46, ylim=c(-2,2), main="After_segN")
 matplot(seg, pch=46, ylim=c(-2,2), col='red', add=TRUE)
 legend("bottomright", bty = "n", pch=20, c("Original data values", "Segment medians"), col=c("black", "red"))
 

[Package aCGH.Spline version 2.2 Index]