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ICASSP
2007
IEEE

Wavelet Footprints and Sparse Bayesian Learning for DNA Copy Number Change Analysis

9 years 6 months ago
Wavelet Footprints and Sparse Bayesian Learning for DNA Copy Number Change Analysis
Alterations in the number of DNA copies are very common in tumor cells and may have a very important role in cancer development and progression. New array platforms provide means to analyze the copy number by comparing the hybridization intensities of thousands of DNA sections along the genome. However, detecting and locating the copy number changes from this data is a very challenging task due to the large amount of biological processes that affect hybridization and cannot be controlled. This paper proposes a new technique that exploits the key characteristic that the DNA copy number is piecewise-constant along the genome. First, wavelet footprints are used to obtain a basis for representing the DNA copy number that is maximally sparse in the number of copy number change points. Second, Sparse Bayesian Learning is applied to infer the copy number changes from noisy array probe intensities. Results demonstrate that Sparse Bayesian Learning has better performance than matching pursuits...
Roger Pique-Regi, En-Shuo Tsau, Antonio Ortega, Ro
Added 02 Jun 2010
Updated 02 Jun 2010
Type Conference
Year 2007
Where ICASSP
Authors Roger Pique-Regi, En-Shuo Tsau, Antonio Ortega, Robert C. Seeger, Shahab Asgharzadeh
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