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Activity Number: 535 - Contributed Poster Presentations: Section on Statistics in Genomics and Genetics
Type: Contributed
Date/Time: Wednesday, August 1, 2018 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Genomics and Genetics
Abstract #330843
Title: Cross Platform Normalization Method Using Matched Sample
Author(s): Serin Zhang* and Jinfeng Zhang and Jiang Shao and Xing Qiu
Companies: Florida State University and Florida State University and Florida State University and University of Rochester
Keywords: Cross platform; Normalization; Breast Cancer Data; Gene
Abstract:

Utilizing high throughput data stored in public archives not only saves research time and cost but also enhances the power of its statistical support. However, systematic discrepancies obstruct the integration of high throughput data. In this work, we focus on eliminating platform effect among systematic effects while the sample effect (i.e., biological information) are kept intact. Our method employs matched and identical samples which are measured by the different platforms for getting benchmark models. We apply our method to the breast cancer microarray data. Through simulated and real datasets, our method performs better than the existing methods.


Authors who are presenting talks have a * after their name.

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