Joint estimation of copy number variation and reference intensities on multiple DNA arrays using GADA.

ABSTRACT:

Motivation

The complexity of a large number of recently discovered copy number polymorphisms is much higher than initially thought, thus making it more difficult to detect them in the presence of significant measurement noise. In this scenario, separate normalization and segmentation is prone to lead to many false detections of changes in copy number. New approaches capable of jointly modeling the copy number and the non-copy number (noise) hybridization effects across multiple samples will potentially lead to more accurate results.

Methods

In this article, the genome alteration detection analysis (GADA) approach introduced in our previous work is extended to a multiple sample model. The copy number component is independent for each sample and uses a sparse Bayesian prior, w

SUBMITTER: Pique-Regi R 

PROVIDER: S-EPMC2732310 | biostudies-literature | 2009 May

REPOSITORIES: biostudies-literature