normalizeWithinArrays.SNP {beadarraySNP}R Documentation

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

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.

Value

This function returns a SnpSetIllumina object.

Author(s)

Jan Oosting

See Also

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

Examples

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

[Package beadarraySNP version 1.6.0 Index]