fitNaiveGenotypes: Fit naive genotype model from a normal sample

In HenrikBengtsson/aroma.light: Light-Weight Methods for Normalization and Visualization of Microarray Data using Only Basic R Data Types

Fit naive genotype model from a normal sample

Description

Fit naive genotype model from a normal sample.

Usage

## S3 method for class 'numeric'
fitNaiveGenotypes(y, cn=rep(2L, times = length(y)), subsetToFit=NULL,
  flavor=c("density", "fixed"), adjust=1.5, ..., censorAt=c(-0.1, 1.1), verbose=FALSE)

Arguments

y	A numeric vector of length J containing allele B fractions for a normal sample.
cn	An optional numeric vector of length J specifying the true total copy number in \{0,1,2,NA\} at each locus. This can be used to specify which loci are diploid and which are not, e.g. autosomal and sex chromosome copy numbers.
subsetToFit	An optional integer or logical vector specifying which loci should be used for estimating the model. If NULL, all loci are used.
flavor	A character string specifying the type of algorithm used.
adjust	A positive double specifying the amount smoothing for the empirical density estimator.
...	Additional arguments passed to findPeaksAndValleys().
censorAt	A double vector of length two specifying the range for which values are considered finite. Values below (above) this range are treated as -Inf (+Inf).
verbose	A logical or a Verbose object.

Value

Returns a list of lists.

Author(s)

Henrik Bengtsson

See Also

To call genotypes see callNaiveGenotypes(). Internally findPeaksAndValleys() is used to identify the thresholds.

HenrikBengtsson/aroma.light documentation built on July 3, 2023, 1:57 a.m.