- Team Lead:
- Christy LaFlamme, St. Jude Graduate Student
- Team Members:
- Nadhir Djekidel, Center for Applied Bioinformatics
- Pandurang Kolekar, Computational Biology
- Wojciech Rosikiewicz, Center for Applied Bioinformatics
DNA methylation is an epigenetic modification that regulates gene expression, the dysregulation of which can cause various diseases. DNA methylation generally occurs at CpG sites, and >850,000 of these CpG sites can be readily assessed from genome-wide, cost-effective methylation arrays. However, few pipelines exist for analyzing and visualizing methylation array data, particularly with an emphasis on rare, disease-causing differentially methylated regions (DMRs). MethMiner is a convenient pipeline to process, analyze, and visualize methylation array data. MethMiner takes raw iDAT files as input, performs quality control/normalization, and uses a window analysis script to perform outlier DMR analysis on autosomes and sex chromosomes. DMRs are then annotated to inform functional interpretation. MethMiner also has data visualization capabilities through JupyterDash where the user can interact with their data through dimensionality reduction plots, DMR annotation breakdowns, and a genomic track browser. Ultimately, MethMiner seeks to provide an easily accessible and convenient methylation array pipeline, thereby expediting DNA methylation discoveries in disease research that can be translated into the clinic.