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Article
Estimating Shared Copy Number Aberrations for Array CGH Data: the Linear-Median Method
Centre for Statistical & Survey Methodology Working Paper Series
  • Yan-Xia Lin, University of Wollongong
  • V. Baladandayuthapani, University of Texas
  • V Bonato, Pfizer Global Research and Development, USA
  • K A Do, University of Texas
Publication Date
1-1-2010
Abstract
Motivation: Existing methods for estimating copy number variations in array comparative genomic hybridization (aCGH) data are limited to estimations of the gain/loss of chromosome regions for single sample analysis. We propose the linear-median method for estimating shared copy numbers in DNA sequences across multiple samples, demonstrate its operating characteristics through simulations and applications to real cancer data, and compare it to two existing methods. Results: Our proposed linear-median method has the power to estimate common changes that appear at isolated single probe positions or very short regions. Such changes are hard to detect by current methods. This new method shows a higher rate of true positives and a lower rate of false positives. The linear-median method is non-parametric and hence is more robust in estimating copy number. Additionally, the linear-median method is easily computable for practical aCGH data sets compared to other copy number estimation methods. Supplementary Information: Supporting materials are available at Cancer Informatics online.
Citation Information
Yan-Xia Lin, V. Baladandayuthapani, V Bonato and K A Do. "Estimating Shared Copy Number Aberrations for Array CGH Data: the Linear-Median Method" (2010)
Available at: http://works.bepress.com/yan-xia_lin/18/