Activity Number:
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190
- Session on Semi-Supervised and Unsupervised Learning
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Type:
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Contributed
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Date/Time:
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Tuesday, August 4, 2020 : 10:00 AM to 2:00 PM
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Sponsor:
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Biometrics Section
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Abstract #313080
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Title:
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Identifying Transgenerational Patterns of Correlated Methylation Sites
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Author(s):
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Xichen Mou* and Hongmei Zhang and Wilfried Karmaus and Hasan Arshad and John Holloway
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Companies:
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University of Memphis and University of Memphis and University of Memphis and University of Southampton and University of Southampton
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Keywords:
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DNA Methylation transmission;
clustering;
EM;
Beta regression
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Abstract:
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DNA methylation can be transmitted across generations. This paper proposes a clustering method to identify the transgenerational patterns from parents to their offsprings. Motivated by the potential of correlation between CpG sites, we use the multivariate generalized beta distribution to model the block-wise correlation structure among CpGs. A stochastic EM algorithm is implemented to estimate the parameters and BIC criterion is applied to determine the optimal number of clusters. Simulations demonstrate the feasibility of the proposed method. We further apply the approach to cluster DNA methylation data generated from a cohort study on asthma and allergic diseases.
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Authors who are presenting talks have a * after their name.