Presented By: Department of Computational Medicine and Bioinformatics DCMB
DCMB Tools and Technology Seminar by Sophia Luo (Biostatistics)
“MethylModes: Intuitive Detection of Multimodal Distributions in DNA Methylation Data”
Tool Link: https://github.com/lutiffan/methylModes
Abstract
MethylModes is an R package and Shiny application to identify multimodal distributions in human DNA methylation at individual CpG sites. Multimodal distributions, which can be the result of nearby genetic variation, environmental exposures or assay artifacts, are susceptible to confounding and important to identify for methylation analysis. We developed MethylModes to robustly identify multimodality in beta value distributions using an intuitive algorithm that avoids stringent modeling assumptions. MethylModes is easily incorporated into existing quality control pipelines of array-based DNA methylation data.
Abstract
MethylModes is an R package and Shiny application to identify multimodal distributions in human DNA methylation at individual CpG sites. Multimodal distributions, which can be the result of nearby genetic variation, environmental exposures or assay artifacts, are susceptible to confounding and important to identify for methylation analysis. We developed MethylModes to robustly identify multimodality in beta value distributions using an intuitive algorithm that avoids stringent modeling assumptions. MethylModes is easily incorporated into existing quality control pipelines of array-based DNA methylation data.