A Bayesian analysis for identifying DNA copy number variations using a compound poisson process

Jie Chen, Ayten Yiǧiter, Yu Ping Wang, Hong Wen Deng

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

To study chromosomal aberrations that may lead to cancer formation or genetic diseases, the array-based Comparative Genomic Hybridization (aCGH) technique is often used for detecting DNA copy number variants (CNVs). Various methods have been developed for gaining CNVs information based on aCGH data. However, most of these methods make use of the log-intensity ratios in aCGH data without taking advantage of other information such as the DNA probe (e.g., biomarker) positions/distances contained in the data. Motivated by the specific features of aCGH data, we developed a novel method that takes into account the estimation of a change point or locus of the CNV in aCGH data with its associated biomarker position on the chromosome using a compound Poisson process. We used a Bayesian approach to derive the posterior probability for the estimation of the CNV locus. To detect loci of multiple CNVs in the data, a sliding window process combined with our derived Bayesian posterior probability was proposed. To evaluate the performance of the method in the estimation of the CNV locus, we first performed simulation studies. Finally, we applied our approach to real data from aCGH experiments, demonstrating its applicability.

Original languageEnglish (US)
Article number268513
JournalEurasip Journal on Bioinformatics and Systems Biology
Volume2010
DOIs
StatePublished - Nov 22 2010

Fingerprint

DNA Copy Number Variations
Compound Poisson Process
Comparative Genomic Hybridization
Bayes Theorem
Comparative Genomics
Bayesian Analysis
DNA
Biomarkers
Locus
DNA Probes
Chromosomes
Aberrations
Posterior Probability
Inborn Genetic Diseases
Sliding Window
Chromosome Aberrations
Change Point
Aberration
Bayesian Approach
Chromosome

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Computer Science Applications
  • Computational Mathematics

Cite this

A Bayesian analysis for identifying DNA copy number variations using a compound poisson process. / Chen, Jie; Yiǧiter, Ayten; Wang, Yu Ping; Deng, Hong Wen.

In: Eurasip Journal on Bioinformatics and Systems Biology, Vol. 2010, 268513, 22.11.2010.

Research output: Contribution to journalArticle

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