Activity Number:
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360
- Contributed Poster Presentations: Section on Bayesian Statistical Science
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Type:
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Contributed
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Date/Time:
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Wednesday, August 5, 2020 : 10:00 AM to 2:00 PM
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Sponsor:
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Section on Bayesian Statistical Science
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Abstract #313953
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Title:
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A Nested Clustering Method to Detect and Cluster Transgenerational DNA Methylation Sites via Beta Regressions
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Author(s):
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Jiajing Wang* and Hongmei Zhang and Shengtong Han
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Companies:
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University of Memphis and University of Memphis and University of Wisconsin, Milwaukee
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Keywords:
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Bayesian;
Clustering;
Heterogeneity;
Beta regression;
Transgenerational transmission
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Abstract:
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Transgenerational transmission of epigenetic marks such as DNA methylation (DNAm) is one possible mechanism explaining observed phenotypic patterns. Little is known at the population level regarding the strength of DNAm transmission. Via beta regressions, we propose a nested Bayesian clustering method to identify DNA methylation (DNAm) sites (CpG sites) such that DNAm is transmitted from one generation to the next, and to study heterogeneity (via clustering) among CpG sites with DNAm transmitted. The number of clusters was defined by use of the screen plot of DICs with each DIC corresponding to a specific number of clusters. We simulated 100 MC replicates to the DNA methylation data composed of 650 CpG sites of 100 mother-father-infant triads in two clusters and three clusters scenarios. We also evaluate our method by increasing the sample size and the number of CpG sites. The high median of probability of correctly detecting the transmission status over 100 MC replicates (range from 0.85 to 0.99) and the high median of sensitivity and specificity of clustering (range from 0.98 to 1) demonstrate and evaluate the applicability of the method. We further apply the method to more than
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Authors who are presenting talks have a * after their name.