normalizeData: Normalize the data set

View source: R/functions_processingQC.R

normalizeDataR Documentation

Normalize the data set

Description

This function (from functions_processing) normalizes the data in the AffyBatch object provided. Currently, GCRMA, RMA, and PLIER normalization are supported. For GCRMA, fast normalization is not used, as this gives unreliable results. For PLIER, justPlier (plier Bioconductor package) is used, with the "together" option for arrays having perfect match and mismatch probes, and the "PMonly" option for arrays with perfect match probes only. When normalization per experimental group is selected, the function makes sure that still one normalized data object including all arrays is returned. In case customCDF is TRUE, annotation is updated using BrainArray custom cdf environments, before proceeding with the normalization (and summarisation of probe expressions into probeset expressions). To update the annotation, a sub call is made to the addUpdatedCDFenv function.

Usage

normalizeData(
  Data,
  normMeth = "",
  perGroup = FALSE,
  experimentFactor = NULL,
  customCDF = TRUE,
  species = NULL,
  CDFtype = NULL,
  aType = NULL,
  isOligo = FALSE,
  WIDTH = 1000,
  HEIGHT = 1414
)

Arguments

Data

(Status: required) The raw data object (datatype: AffyBatch)

normMeth

(Status: required, Default: "") String indicating the normalization method used. Possible values: RMA, GCRMA, PLIER or none. (datatype: character)

perGroup

(Status: optional, Default: FALSE) Should normalization be performed per experimental group (e.g. when global differences are expected between groups) or for the dataset as a whole? (datatype: logical)

experimentFactor

(Status: required if perGroup is TRUE , Default: NULL) The factor of groups. (datatype: factor)

customCDF

(Status: optional, Default: TRUE) Should annotation of the chip be updated before normalizing the data (and building the probesets out of the separate probes)? If requested, this is done using BrainArray updated cdf environments, c.f. addUpdatedCDFenv (datatype: logical)

species

(Status: required when customCDF is TRUE, c.f. addUpdatedCDFenv, Default: NULL) The species associated with the chip type. (datatype: character)

CDFtype

(Status: required when customCDF is TRUE, c.f. addUpdatedCDFenv, Default: NULL) The type of custom cdf requested. (datatype: character)

aType

(Status: optional, Default: NULL) String indicating the type of the current chip, either “PMMM” for chips with perfect match and mismatch probes, or “PMonly” for chips with perfect match probes only. Required if normMeth is “PLIER”. (datatype: character)

isOligo

(Status: optional, Default:FALSE) is Oligo array or not (datatype: logical)

WIDTH

(Status: optional, Default:1000) png image width (datatype: number)

HEIGHT

(Status: optional, Default:1414) png image height (datatype: number)

Value

A normalized data object (datatype: ExpressionSet). It also returns A reference sheet (PNG file) indicating the cdf annotation (cdfName) used, the normalization method used, and if this is the case stating that normalization has been performed per experimental group

Examples

#By default, the script will call, if customCDF is TRUE:
#normData <- normalizeData(rawData, normMeth,
#perGroup=(normOption1=="group"), experimentFactor, customCDF,
#species, CDFtype)
#or, if customCDF is FALSE:
#normData <- normalizeData(rawData, normMeth,
#perGroup=(normOption1=="group"), experimentFactor, customCDF)

ammar257ammar/ArrayAnalysis-Bioconductor documentation built on Jan. 29, 2024, 7:21 a.m.