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aroma.affymetrix (version 2.11.1)

doCRMAv1: Estimation and assessment of raw copy numbers at the single locus level (CRMA v1)

Description

Estimation and assessment of raw copy numbers at the single locus level (CRMA v1) based on [1]. The algorithm is processed in bounded memory, meaning virtually any number of arrays can be analyzed on also very limited computer systems.

Usage

## S3 method for class 'AffymetrixCelSet':
doCRMAv1(csR, shift=+300, combineAlleles=TRUE, lengthRange=NULL, arrays=NULL, drop=TRUE,
  verbose=FALSE, ...)
  ## S3 method for class 'default':
doCRMAv1(dataSet, ..., verbose=FALSE)
  ## S3 method for class 'default':
doASCRMAv1(...)

Arguments

csR, dataSet
An AffymetrixCelSet (or the name of an AffymetrixCelSet).
shift
An tuning parameter specifying how much to shift the probe signals before probe summarization.
combineAlleles
A logical specifying whether allele probe pairs should be summed before modelling or not.
lengthRange
An optional numeric vector of length two passed to FragmentLengthNormalization.
arrays
A integer vector specifying the subset of arrays to process. If NULL, all arrays are considered.
drop
If TRUE, the summaries are returned, otherwise a named list of all intermediate and final results.
verbose
See Verbose.
...
Additional arguments used to set up AffymetrixCelSet (when argument dataSet is specified).

Value

Allele-specific or only total-SNP signals

If you wish to obtain allele-specific estimates for SNPs, which are needed to call genotypes or infer parent-specific copy numbers, then use argument combineAlleles=FALSE. Total copy number signals are still available. If you know for certain that you will not use allele-specific estimates, you will get slightly less noisy signals (very small difference) if you use combineAlleles=TRUE.

doASCRMAv1(...) is a wrapper for doCRMAv1(..., combineAlleles=FALSE).

References

[1] H. Bengtsson, R. Irizarry, B. Carvalho & T.P. Speed. Estimation and assessment of raw copy numbers at the single locus level, Bioinformatics, 2008.

See Also

For CRMA v2 (recommended by authors), which is a single-array improvement over CRMA v1, see doCRMAv2().