Oregon State University

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Statistical and Epidemiological Issues in Analysis of DNA Methylation Microarray Data

E. Andres Houseman, Sc.D. Assoc. Prof. of Biostatistics College of Health and Human Sciences, OSU

Monday, February 20, 2012 3:55 PM - 5:00 PM

Epigenetics is the study of heritable changes in gene function unexplained by changes in DNA sequence, and is one of the modes by which environment is thought to interact with genetics.  As such, epigenetic alterations constitute an important type of genome-scale variable mediating between environment and disease, and present unique opportunities for conducting epidemiological research.  The most commonly studied type of epigenetic alteration in population studies is cytosine methylation, which is a well-recognized mechanism of gene silencing. Microarrays are now being used to study DNA methylation at a large number of cytosine targets; for example, the older Illumina Infinium platform assesses DNA methylation at 27,000 loci, while the newer Infinium array measures DNA methylation at over 485,000 sites.  In this talk, we introduce the biology of DNA methylation and present two related issues that arise in microarray data analysis, unique to investigation of the methylome.  The first concerns variation in the selection of cytosine targets across different genes with respect to their "geographic features", which can lead to bias in estimates of methylome alterations along predefined biological pathways if conventional gene set enrichment methods, developed for mRNA expression microarrays, are employed without proper stratification.  Therefore, we propose a new, stratified gene set enrichment statistic that is more appropriate for analysis of DNA methylation data.  The second issue concerns the interpretation of methylome alterations when biological samples consist of mixtures of cells (e.g. whole blood) and apparent alterations in the methylome may be induced purely by changes in the distribution of component cell types.  We therefor propose a novel statistical method for detecting the latter process.  In general, analysis and interpretation of DNA methylation microarrays requires a deep understanding of the biology of the methylome and the development of statistical tools that appropriately address its unique features.

Covell Hall (campus map)
221
Notocha Coe
1 541 737 3611
coen at stat.oregonstate.edu
Statistics (Science)
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