FBN (version 1.5.2)

FBN.histogramMaxima: Local maxima of the histogram of SNP microarray data

Description

Finds at most 6 of the local maxima of the histogram of the inputData representing the SNP microarray data. Firstly, the function finds all local maxima onto the histogram, and finally removes those that are closer than minSpan. The histogram is estimated with equi-spaced breaks (also the default), defined by breaksData (see the documentation of hist for more details).

Usage

FBN.histogramMaxima(inputData, minSpan, breaksData)
FBN.histogramMaxima(inputData, minSpan = 0.2, breaksData = NULL)

Value

Returns a vector containing at most 6 values of the inputData in which the histogram shows local maxima.

Arguments

inputData

A vector of SNP microarray values for which the local maxima of the histogram are desired

minSpan

The minimum distance separating consecutive local maxima. If minSpan is negative, then a smoothing filter is applied on the histogram to reduce its noise, and therefore, estimates the most significative maxima.

breaksData

One of:

• a vector giving the breakpoints between histogram cells,

• a single number giving the number of cells for the histogram,

• a character string naming an algorithm to compute the number of cells (see the Details section of hist),

• a function to compute the number of cells.

Author

Adrian Andronache
Luca Agnelli

Details

This function has been designed based on SNP microarray data and FISH resolution. As in FISH analyses high numbers of signals do not allow a correct identification of discrete CNs, an empirical number of no more than 6 local maxima is therefore imposed. These maxima are used to initialize the k-means algorithm to determine the CN clusters.

See Also

hist, FBNormalization

Examples

require(stats)
require(graphics)

x = c(rnorm(1000, 1, .2), rnorm(1000, 2, .2))
y = FBN.histogramMaxima(x, minSpan = .1)
h = hist(x)
par(new = TRUE)
plot(y,vector(mode=mode(y), length = length(y)), xlim = c(min(h$breaks), 
 	max(h$breaks)), ylim = c(0,max(h$counts)), xlab = NA, ylab = NA, 
 	col = 'red' )


x = c(1, 2, 2, 3, 4, 5, 5, 5, 6, 7, 8, 9, 10, 10, 10, 11)
y = FBN.histogramMaxima(x, minSpan = 3, breaksData = 100)
h = hist(x, 100)
par(new = TRUE)
plot(y,vector(mode=mode(y), length = length(y)), xlim = c(min(h$breaks), 
 	max(h$breaks)), ylim = c(0,max(h$counts)), xlab = NA, ylab = NA, 
 	col = 'red' )