BeadLevelNormalise {beadarray} | R Documentation

## Bead Level Normalisation

### Description

A single function which combines the steps of reading bead level data, normalisation and summarising.

### Usage

    BeadLevelNormalise(targets, imageManipulation="sharpen",
                 backgroundCorrect="none", probes=NULL,imagesPerArray=2)

### Arguments

`targets` | A targets object defining which bead level files to read
`imageManipulation` | string specifying what image processing steps to use to get foreground intensities
`backgroundCorrect` | string specifying what background correction (if any) to do
`probes` | an optional list of ProbeIDs to use summarise
`imagesPerArray` | integer to specify how many images comprise each array. Used when we have to strips per array on the Human-Ref6 arrays

### Details

This is a memory and space efficient method for reading and normalising a large number of arrays at the bead level and based on the work of Henrik Bengsson. It comprises of a pre-processing, normalisation and probe summary.

Quality control should be performed prior to this function is order to identify any outlier arrays and decide upon an image processing strategy.

In the first stage of the function, we read each array in turn using the image processing steps specified by the imageManipulation and backgroundCorrect parameters and keep a running total of the value of each quantile of the distribution.

For Human-6 arrays where each array is in fact two images, we read each image separately and bind together the resulting intensities before computing quantiles.

Each array is then read a second time, normalised to the target distribution and then summarised.

### Value

ExpressionSetIllumina containing summarised data

### Author(s)

Mark Dunning

[Package beadarray version 1.4.0 Index]