HULK: HULK - Bead Array Normalization by NEighbourhood Residuals

In markdunning/beadarray-devel: Quality assessment and low-level analysis for Illumina BeadArray data

Description

Normalizes an probe intensities by calculating a weighted average residual based on the residuals of the surrounding probes.

Usage

HULK(BLData, array = 1, neighbours = NULL, invasions = 20, useLocs = TRUE, weightName = "wts", transFun = logGreenChannelTransform, outlierFun = illuminaOutlierMethod)

Arguments

BLData	An object of class beadLevelData-class
array	integer specifying which section/array to process
neighbours	A Neighbours matrix. Optional - if left NULL, it will be computed.
invasions	Integer - Number of invasions used when identifying neighbouring beads.
useLocs	If information from an associated .locs file is to be used. If available using a .locs file can improve both the speed and accuracy of determining the network of neighbouring beads.
weightName	Column name where bead weights are to be taken from.
transFun	Transformation function.
outlierFun	Name or definition for the function to be used to calculated outliers.

Details

HULK is a method of intensity normalization based upon the BASH framework. Firstly For each bead a local neighbourhood of beads is determined, using the same process as the other BASH functions.

For each bead a weighted average residual is calculated. The average residual is calculated as the sum of the residuals for each bead in the neighbourhood, divided by 1 plus the number of invasions it took to reach that bead. This calculation is made by a call to HULKResids.

The average residuals are then subtracted from each bead and a vector of the resulting corrected intensities object is returned. These corrected intensities can be saved in the original beadLevelData object using insertBeadData

Value

A vector of corrected intensities.

Author(s)

Mike Smith

References

Lynch AG, Smith ML, Dunning MJ, Cairns JM, Barbosa-Morais NL, Tavare S. beadarray, BASH and HULK - tools to increase the value of Illumina BeadArray experiments. In A. Gusnato, K.V. Mardia, & C.J. Fallaize (eds), Statistical Tools for Challenges in Bioinformatics. 2009 pp. 33-37. Leeds, Leeds University Press.

See Also

BASH, insertBeadData, logGreenChannelTransform, squeezedVarOutlierMethod, illuminaOutlierMethod

Examples

## Not run: 

    if(require(beadarrayExampleData)){

    	
	data(exampleBLData)
	o <- HULK(exampleBLData, 1)

}


## End(Not run)

markdunning/beadarray-devel documentation built on May 21, 2019, noon