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A statistical method for excluding non-variable CpG sites in high-throughput DNA methylation profiling |
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| Authors: | Hailong Meng Andrew R Joyce Daniel E Adkins Priyadarshi Basu Yankai Jia Guoya Li Tapas K Sengupta Barbara K Zedler E Lenn Murrelle Edwin JCG van den Oord |
| Affiliation: | (1) Altria Client Services, Research Development & Engineering, 601 E. Jackson Street, Richmond, VA 23219, USA;(2) Venebio Group, LLC, Virginia Bio-Technology Research Park, Richmond, Virginia, USA;(3) Center for Biomarker Research and Personalized Medicine, School of Pharmacy, Virginia Commonwealth University, Richmond, VA 23298, USA;(4) Memorial Sloan-Kettering Cancer Center, 415 East 68th Street, New York, NY 10021, USA;(5) Bon Secours Virginia Health System, 14331 Roderick Ct., Midlothian, VA 23113, USA;(6) American Type Culture Collection, 10801 University Blvd, Manassas, VA 20110, USA |
| Abstract: | BackgroundHigh-throughput DNA methylation arrays are likely to accelerate the pace of methylation biomarker discovery for a wide variety of diseases. A potential problem with a standard set of probes measuring the methylation status of CpG sites across the whole genome is that many sites may not show inter-individual methylation variation among the biosamples for the disease outcome being studied. Inclusion of these so-called "non-variable sites" will increase the risk of false discoveries and reduce statistical power to detect biologically relevant methylation markers. |
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