Bayesian joint estimation of CN and LOH aberrations

Abstract

SNP-microarrays are able to measure simultaneously both copy number and genotype at several single nucleotide polymorphism positions. Combining the two data, it is possible to better identify genomic aberrations. For this purpose, we propose a Bayesian piecewise constant regression which infers the type of aberration occurred, taking into account all the possible influence in the microarray detection of the genotype, resulting from an altered copy number level. Namely, we model the distributions of the detected genotype given a specific genomic alteration and we estimate the hyper-parameters used on public reference datasets. © 2009 Springer Berlin Heidelberg.