Development of a Normalization Algorithm for Array Comparative Genomic Hybridization
Date Issued
2007
Date
2007
Author(s)
Chen, Hung-I Harry
DOI
en-US
Abstract
Genomic instability is one of fundamental factors in tumorigenesis and tumor progression. Many studies have shown that copy-number abnormalities at the DNA level are important in the pathogenesis of cancer. Array Comparative Genomic Hybridization (array CGH), developed based on expression microarray technology, can reveal the chromosomal aberrations in segmental copies at a high-resolution. However, due to the nature of array CGH, many standard expression data processing tools, such as data normalization, often failed to yield satisfactory results. We demonstrate a novel array CGH normalization algorithm, which provides an accurate array CGH data normalization by utilizing the dependency of neighboring probe measurements in array CGH experiments.
To facilitate the study, we have developed a Hidden Markov Model (HMM) to simulate a series of array CGH experiments with random DNA copy number alterations that can be used to validate the performance of our normalization. In addition, we applied our algorithm to normalize real data from an array CGH study of CL1-0, CL1-1 and CL1-5 cell lines. CL1-0, CL1-1 and CL1-5 are closely related lung cancer cell lines which are classified according to their differential invasiveness. The normalization made significant improvement over data quality and enhanced the reliability of experimental results. By using this newly developed algorithm, the normalized data showed distinct patterns of DNA copy number alternations among those lung cancer cell lines. Finally, based on this new development; we are establishing a user-friendly web-based system to provide convenient online array CGH data analysis.
Subjects
基因體雜合微陣列
去氧核醣核酸拷貝數
正規化
向心化
隱馬爾可夫模型
Array CGH
DNA copy numbers
Normalization
Centralization
Hidden Markov Model
SDGs
Type
thesis
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