Differentially Aberrant Region Detection in Array CGH Data based on Nearest Neighbor Classification Performance

• Item type: SIG Technical Reports(1)
• 公開日: 2011-03-03
• タイトル: Differentially Aberrant Region Detection in Array CGH Data based on Nearest Neighbor Classification Performance
• タイトル / 言語: en
• タイトル: Differentially Aberrant Region Detection in Array CGH Data based on Nearest Neighbor Classification Performance
• 言語: eng
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_18gh
• 資源タイプ: technical report
• 著者所属: Nagoya Institute of Technology
• 著者所属: Nagoya Institute of Technology
• 著者所属(英): en
• 著者所属(英): Nagoya Institute of Technology
• 著者所属(英): en
• 著者所属(英): Nagoya Institute of Technology
• 著者名: Yuta, Ishikawa; Ichiro, Takeuchi
• 著者名(英): Yuta, Ishikawa; Ichiro, Takeuchi
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Array CGH is a useful technology for detecting copy number aberrations in genome-wide scale. We study the problem of detecting differentially aberrant genomic regions in two or more groups of CGH arrays and estimating the statistical significance of those regions. An important property of array CGH data is that there are spatial correlations among probes, and we need to take this fact into consideration when we develop a computational algorithm for array CGH data analysis. In this paper we first discuss three difficult issues underlying this problem, and then introduce nearest-neighbor multivariate test in order to alleviate these difficulties. Our proposed approach has three advantages. First, it can incorporate the spatial correlation among probes. Second, genomic regions with different sizes can be analyzed in a common ground. And finally, the computational cost can be considerably reduced with the use of a simple trick. We demonstrate the effectiveness of our approach through an application to previously published array CGH data set on 75 malignant lymphoma patients.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Array CGH is a useful technology for detecting copy number aberrations in genome-wide scale. We study the problem of detecting differentially aberrant genomic regions in two or more groups of CGH arrays and estimating the statistical significance of those regions. An important property of array CGH data is that there are spatial correlations among probes, and we need to take this fact into consideration when we develop a computational algorithm for array CGH data analysis. In this paper we first discuss three difficult issues underlying this problem, and then introduce nearest-neighbor multivariate test in order to alleviate these difficulties. Our proposed approach has three advantages. First, it can incorporate the spatial correlation among probes. Second, genomic regions with different sizes can be analyzed in a common ground. And finally, the computational cost can be considerably reduced with the use of a simple trick. We demonstrate the effectiveness of our approach through an application to previously published array CGH data set on 75 malignant lymphoma patients.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AA12055912
• 書誌情報: 研究報告バイオ情報学（BIO）; 巻 2011-BIO-24, 号 3, p. 1-8, 発行日 2011-03-03
• Notice: SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
• 出版者 / 言語: ja
• 出版者: 情報処理学会