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This article is part of the supplement: Selected articles from the IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS) 2011

Open Access Research

A nonparametric Bayesian approach for clustering bisulfate-based DNA methylation profiles

Lin Zhang1, Jia Meng2, Hui Liu1 and Yufei Huang23*

Author Affiliations

1 School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, 221116, China

2 Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, TX 78249, USA

3 Department of Biostatistics, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA

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BMC Genomics 2012, 13(Suppl 6):S20  doi:10.1186/1471-2164-13-S6-S20

Published: 26 October 2012

Additional files

Additional file 1:

Top 20 variable loci (ranked by variance through samples) selected from the methylation profiles of the 55 GBM samples.

Format: DOC Size: 43KB Download file

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Additional file 2:

The number of uncovered clusters and P-value of overall survival analysis for J ∈ {1, 2, ..., 20}. P-value is used to test the Kaplan-Meier confidence.

Format: DOC Size: 33KB Download file

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Open Data