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Activity Number: 186
Type: Contributed
Date/Time: Monday, August 4, 2014 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract #313563
Title: A Classification Approach for DNA Methylation Profiling with Bisulphite Next-Generation Sequencing Data
Author(s): Longjie Cheng*+ and Yu Zhu
Companies: and Purdue University
Keywords: DNA methylation ; Next-generation sequencing ; classification ; FDR ; epigenetics
Abstract:

With the advent of high-throughput sequencing technology, bisulphite-sequencing based DNA methylation profiling methods have emerged as the most promising approaches due to their single-base resolution and genome-wide coverage. However, statistical analysis methods for analyzing this type of methylation data are not well developed. In this paper, we use a mixture model approach to characterize bisulphite-sequencing data, and based on the model, we propose to use a classification based procedure, called the Methylation Status Calling (MSC) procedure, to make binary methylation status calls. The FDR and FNDR of MSC can be estimated. In order to control FDR at any given level, we further develop a FDR-controlling MSC (FMSC) procedure. Both simulation study and real data application are carried out to examine the performance of the proposed procedures. It is shown in our simulation study that the estimates of FDR and FNDR of the MSC procedure are appropriate. Simulation study also demonstrates that the FMSC procedure is valid in controlling FDR at a prespecified level. In the real data application, the MSC procedure exhibits an estimated FDR of 0.1426 and an estimated FNDR of 0.0067.


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