Algorithms to fit the CalMaTe model for a single SNP. Note: These are internal functions of the package. They should not be used elsewhere.
fitCalMaTeV1(dataT, references, fB1=1/3, fB2=2/3, maxIter=50, ...) fitCalMaTeV2(dataT, references, fB1=1/3, fB2=2/3, maxIter=50, ...) fitCalMaTeMedians(dataT, references, fB1=1/3, fB2=2/3,...)
Thresholds for calling genotypes AA, AB, BB from the allele B fractions.
The maximum number of iterations without converging before the algorithm quits.
Returns a 2xI
matrix of calibrated ASCNs.
This is an early version (June 2010-January 2012) of the algorithm described in .
This is the model and algorithm described in .
This version was introduced to decrease the number of "artificial outliers" introduced by CalMaTe for some SNPs due to non-converging or wreak-havoc estimates of the SNP effects. Flavor v2 differ from Flavor v1 as follows:
The estimation of the model parameters are now done solely based on reference samples. In previous versions, some of the initial estimation steps were using also non-reference samples.
For a small number of SNPs, the main CalMaTe scheme for estimating
parameters would not converge or converge poorly. For such SNPs
CalMaTe now falls back to using a plain median estimator,
The above fallback estimator is also used in cases where all samples are identified to be homozygous.
fitCalMaTeMedians() method is used as a fallback method
fitCalMaTeV2(). It fits CalMaTe without using the
 M. Ortiz-Estevez, A. Aramburu, H. Bengtsson, P. Neuvial and A. Rubio, CalMaTe: A method and software to improve allele-specific copy number of SNP arrays for downstream segmentation, Bioinformatics, 2012 [PMC3381965].
These functions are called by
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