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August 2016 A semiparametric Bayesian model for comparing DNA copy numbers
Luis Nieto-Barajas, Yuan Ji, Veerabhadran Baladandayuthapani
Braz. J. Probab. Stat. 30(3): 345-365 (August 2016). DOI: 10.1214/15-BJPS283

Abstract

We propose a two-step method for the analysis of copy number data. We first define the partitions of genome aberrations and conditional on the partitions we introduce a semiparametric Bayesian model for the analysis of multiple samples from patients with different subtypes of a disease. While the biological interest is to identify regions of differential copy numbers across disease subtypes, our model also includes sample-specific random effects that account for copy number alterations between different samples in the same disease subtype. We model the subtype and sample-specific effects using a random effects mixture model. The subtype’s main effects are characterized by a mixture distribution whose components are assigned Dirichlet process priors. The performance of the proposed model is examined using simulated data as well as a breast cancer genomic data set.

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Luis Nieto-Barajas. Yuan Ji. Veerabhadran Baladandayuthapani. "A semiparametric Bayesian model for comparing DNA copy numbers." Braz. J. Probab. Stat. 30 (3) 345 - 365, August 2016. https://doi.org/10.1214/15-BJPS283

Information

Received: 1 January 2014; Accepted: 1 February 2015; Published: August 2016
First available in Project Euclid: 29 July 2016

zbMATH: 1381.92070
MathSciNet: MR3531688
Digital Object Identifier: 10.1214/15-BJPS283

Rights: Copyright © 2016 Brazilian Statistical Association

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Vol.30 • No. 3 • August 2016
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