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Activity Number: 180 - Statistical Methods for Functional Genomic and Epigenomic Data
Type: Contributed
Date/Time: Monday, July 29, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Genomics and Genetics
Abstract #306689 Presentation
Title: Exploring Functional Data Analysis to Identify Differentially Methylated Regions in Plants
Author(s): Mohamed Milad* and Gayla Olbricht
Companies: Arkansas State University , Jonesboro and Missouri Science and Technology University
Keywords: Functional Data; DNA Methylation ; Epigentics

DNA methylation is one of the most widely studied epigenetic modifications that alters gene expression without a DNA sequence change. In mammals, DNA methylation occurs almost exclusively in the context of CpG dinucleotides when a methyl group attaches to the cytosine. In plants, DNA is methylated in three sequence contexts: CG, CHG and CHH (where H=A,T or C).Whole-genome bisulfite sequencing measures methylation levels across the entire genome,enabling genome-wide comparisons between different conditions. Application of Wavelet Functional Analysis (WFA) was implemented in an Arabidopsis thaliana dataset to identify differentially methylated regions (DMRs). The performance of our approach with two alternative methods (M3D,MAGI) is evaluated on simulated data.

Authors who are presenting talks have a * after their name.

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