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Activity Number: 71
Type: Contributed
Date/Time: Sunday, August 3, 2014 : 4:00 PM to 5:50 PM
Sponsor: Biometrics Section
Abstract #313389
Title: Systematic Approach for Detecting Copy Number Variation
Author(s): Ching-Wei Chang*+
Companies: FDA/National Center for Toxicological Research
Keywords: copy number variation ; clustering
Abstract:

Copy number amplifications or deletions in DNA segments contribute to many human diseases. It is critical to identify copy number changes to understand both the genesis and progression of many diseases. There are many existing methods to detect copy number variation that are based on cytogenetic karyotype analysis or high throughput data. These approaches can detect the breakpoints or segments well. However, they are limited by their inability to determine the actual copy number. A systematic procedure is proposed for determining the number of groups of copy number intensities. After applying the selected segmentation method to detect breakpoints, a novel clustering algorithm is proposed to determine the number of copy number variations. The performance of the proposed procedure is evaluated by both simulated and real data. The experimental results showed that both the proposed methodology can correctly cluster copy number groups through an automated procedure.


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