Poster #12 - Hongxiang Fu

KnowYourCG: Enabling CpG-centric Interpretation of Sparse DNA Methylomes

Hongxiang Fu1,* David C Goldberg1,* Daniel Atkins1, Ethan Moyer1, Chin Nien Lee2, Yanxiang Deng2, Wanding Zhou1 1Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, PA, 19104, USA, 2Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA *Authors contributed equally.

Decoding DNA methylomes for biological insights is critical in epigenetics research. We present KnowYourCG, a data interpretation framework designed for functional DNA methylation analysis. Unlike existing tools that target genes or genomic intervals, KnowYourCG analyzes CpG dinucleotides, featuring automated supervised screenings of diverse biological and technical influences, including sequence motifs, transcription factor binding, histone modifications, replication timing, cell-type-specific methylation, and trait associations. Leveraging innovative infrastructure that rapidly screens and investigates thousands of knowledgebases, KnowYourCG addresses the challenges of data sparsity in various methylation datasets, including low-pass Nanopore sequencing, single-cell DNA methylomes, 5-hydroxymethylation profiles, spatial DNA methylation maps, and array-based datasets for epigenome-wide association studies and epigenetic clocks. Applying KnowYourCG to these datasets provides new perspectives on cell differentiation, cancer origins, epigenome-trait associations, and technical issues such as array artifacts, single-cell batch effects, and Nanopore 5hmC detection accuracy. Our tool simplifies large-scale methylation analysis and integrates seamlessly with standard assay technologies.