https://scholars.lib.ntu.edu.tw/handle/123456789/523738
Title: | A probe-density-based analysis method for array CGH data: Simulation, normalization and centralization | Authors: | Chen, H.-I.H. Hsu, F.-H. Jiang, Y. Tsai, M.-H. PAN-CHYR YANG Meltzer, P.S. Chuang, E.Y. MONG-HSUN TSAI Yang, Pan-Chyr CHUANG, ERIC YAO-YU ERIC YAO-YU CHUANG |
Issue Date: | 2008 | Journal Volume: | 24 | Journal Issue: | 16 | Start page/Pages: | 1749-1756 | Source: | Bioinformatics | Abstract: | Motivation: Genomic instability is one of the 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 (aCGH), developed based on expression microarray technology, can reveal the chromosomal aberrations in segmental copies at a high resolution. However, due to the nature of aCGH, many standard expression data processing tools, such as data normalization, often fail to yield satisfactory results. Results: We demonstrated a novel aCGH normalization algorithm, which provides an accurate aCGH data normalization by utilizing the dependency of neighboring probe measurements in aCGH experiments. To facilitate the study, we have developed a hidden Markov model (HMM) to simulate a series of aCGH experiments with random DNA copy number alterations that are used to validate the performance of our normalization. In addition, we applied the proposed normalization algorithm to an aCGH study of lung cancer cell lines. By using the proposed algorithm, data quality and the reliability of experimental results are significantly improved, and the distinct patterns of DNA copy number alternations are observed among those lung cancer cell lines. ? The Author 2008. Published by Oxford University Press. All rights reserved. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-49549100274&doi=10.1093%2fbioinformatics%2fbtn321&partnerID=40&md5=cacaf79eeb1b352184f85cd002f52700 https://scholars.lib.ntu.edu.tw/handle/123456789/523738 |
ISSN: | 1367-4803 | DOI: | 10.1093/bioinformatics/btn321 | SDG/Keyword: | accuracy; algorithm; breast cancer; cancer cell culture; comparative genomic hybridization; conference paper; controlled study; data analysis; DNA replication; hidden Markov model; human; human cell; lung cancer; microarray analysis; numerical chromosome aberration; priority journal; reliability; simulation; statistical analysis; validation process; Base Sequence; Chromosome Mapping; Computer Simulation; DNA Probes; Gene Dosage; Models, Genetic; Molecular Sequence Data; Oligonucleotide Array Sequence Analysis; Sequence Alignment; Sequence Analysis, DNA [SDGs]SDG3 |
Appears in Collections: | 醫學系 |
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