Stationary wavelet packet transform and dependent laplacian bivariate shrinkage estimator for array-CGH data smoothing

Nha H. Nguyen, Heng Huang, Soontorn Oraintara, An Vo

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Array-based comparative genomic hybridization (aCGH) has merged as a highly efficient technique for the detection of chromosomal imbalances. Characteristics of these DNA copy number aberrations provide the insights into cancer, and they are useful for the diagnostic and therapy strategies. In this article, we propose a statistical bivariate model for aCGH data in the stationary wavelet packet transform (SWPT) and apply this bivariate shrinkage estimator into the aCGH smoothing study. Because our new dependent Laplacian bivariate shrinkage estimator covers the dependency between wavelet coefficients and the shift invariant SWPT results include both low- and high-frequency information, our dependent Laplacian bivariate shrinkage estimator based SWPT method (named as SWPT-LaBi) has fundamental advantages to solve aCGH data smoothing problem compared to other methods. In our experiments, two standard evaluation methods, the Root Mean Squared Error (RMSE) and the Receiver Operating Characteristic (ROC) curve, are calculated to demonstrate the performance of our method. In all experimental results, our SWPT-LaBi method outperforms the previous most commonly used aCGH smoothing algorithms on both synthetic data and real data. Meantime, we also propose a new synthetic data generation method for aCGH smoothing algorithms evaluation. In our new data model, the noise from real aCGH data is extracted and used to improve synthetic data generation.

Original languageEnglish (US)
Pages (from-to)139-152
Number of pages14
JournalJournal of Computational Biology
Volume17
Issue number2
DOIs
StatePublished - Feb 1 2010
Externally publishedYes

Fingerprint

Wavelet Packet Transform
Shrinkage Estimator
Wavelet Analysis
Comparative Genomics
Comparative Genomic Hybridization
Smoothing
Dependent
Synthetic Data
Smoothing Algorithm
Aberrations
Data structures
DNA
Receiver Operating Characteristic Curve
Wavelet Coefficients
Statistical Models
Evaluation Method
Aberration
Mean Squared Error
ROC Curve
Data Model

Keywords

  • Array comparative genomic hybridization
  • DNA copy number
  • Smoothing
  • Stationary wavelet packet transform

ASJC Scopus subject areas

  • Modeling and Simulation
  • Molecular Biology
  • Genetics
  • Computational Theory and Mathematics
  • Computational Mathematics

Cite this

Stationary wavelet packet transform and dependent laplacian bivariate shrinkage estimator for array-CGH data smoothing. / Nguyen, Nha H.; Huang, Heng; Oraintara, Soontorn; Vo, An.

In: Journal of Computational Biology, Vol. 17, No. 2, 01.02.2010, p. 139-152.

Research output: Contribution to journalArticle

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