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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/51082


    Title: An all-statistics, high-speed algorithm for the analysis of copy number variation in genomes
    Authors: Chen,CH;Lee,HC;Ling,Q;Chen,HR;Ko,YA;Tsou,TS;Wang,SC;Wu,LC;Lee,HC
    Contributors: 系統生物與生物資訊研究所
    Keywords: ARRAY-CGH DATA;CIRCULAR BINARY SEGMENTATION;OLIGONUCLEOTIDE MICROARRAY;HYBRIDIZATION DATA;ACCURATE
    Date: 2011
    Issue Date: 2012-03-27 18:20:53 (UTC+8)
    Publisher: 國立中央大學
    Abstract: Detection of copy number variation (CNV) in DNA has recently become an important method for understanding the pathogenesis of cancer. While existing algorithms for extracting CNV from microarray data have worked reasonably well, the trend towards ever larger sample sizes and higher resolution microarrays has vastly increased the challenges they face. Here, we present Segmentation analysis of DNA (SAD), a clustering algorithm constructed with a strategy in which all operational decisions are based on simple and rigorous applications of statistical principles, measurement theory and precise mathematical relations. Compared with existing packages, SAD is simpler in formulation, more user friendly, much faster and less thirsty for memory, offers higher accuracy and supplies quantitative statistics for its predictions. Unique among such algorithms, SAD's running time scales linearly with array size; on a typical modern notebook, it completes high-quality CNV analyses for a 250 thousand-probe array in similar to 1 s and a 1.8 million-probe array in similar to 8 s.
    Relation: NUCLEIC ACIDS RESEARCH
    Appears in Collections:[系統生物與生物資訊研究所] 期刊論文

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