beadarraySNP (version 1.38.0)

normalizeWithinArrays.SNP: Within Array normalization

Description

Perform within array normalization on Illumina Golden Gate bead arrays.

Usage

normalizeWithinArrays.SNP(object, callscore=0.5, normprob=0.5, quantilepersample=FALSE, relative=FALSE, fixed=FALSE, useAll=FALSE, subsample="OPA", Q.scores="callProbability")

Arguments

object

class SnpSetIllumina.

callscore

numeric with range 0:1, threshold for probe inclusion.

normprob

numeric with range 0:1, target quantile for normalization. The default is to divide the sample intensities by the median of the selected subset.

quantilepersample

logical. If TRUE then the threshold is determined for each sample, else it is experiment wide. This is only relevant when fixed is FALSE.

relative

logical. If TRUE then the ratio of GCS and GTS is used, else only the GCS is used as the quality score.

fixed

logical. If TRUE then callscore is the fixed threshold for the quality score, else the probes above the quantile callscore are used.

useAll

logical. If TRUE then all probes in the dataset are eligible as the invariant set, else only the heterozygous SNPs.

subsample

factor or column name in featureData slot, the levels of the factor are treated separately.

Q.scores

name of assayData() element, or numeric matrix of appropriate size. Quality scores to select high quality SNPs

Value

This function returns a SnpSetIllumina object.

Details

The function uses high quality heterozygous SNPs as an invariant set with the assumption that these have the highest probability of coming from unaffected regions of the genome. Most of the arguments are used to determine the quality of the call.

See Also

SnpSetIllumina,normalizeLoci.SNP, backgroundCorrect.SNP,normalizeBetweenAlleles.SNP

Examples

  data(chr17.260)
  data.nrm <- normalizeWithinArrays.SNP(chr17.260)