Abstract LB345: NANOME: A Nextflow pipeline for haplotype-aware allele-specific consensus DNA methylation detection by nanopore long-read sequencing

Abstract Nanopore long-read sequencing has expanded the capacity of long-range, single-base, and single-molecule DNA-methylation (DNAme) detection and haplotype-aware allele-specific epigenetic phasing. Previously, we benchmarked and ranked the robustness of seven computational tools for DNAme detection using nanopore sequencing. Overall, the top performers were Megalodon, Nanopolish, DeepSignal and Guppy. However, these algorithms exhibit lower performance at regions with discordant non-singleton DNAme patterns, intergenic regions, low CG density regions, and repetitive regions compared to genome-wide region. Furthermore, long-read sequencing analysis of mammalian genomes requires higher computational resources than next-generation sequencing. To address these issues, we developed NANOME, the first cloud-compatible, Nextflow-based container environment for consensus DNAme detection. We designed a consensus DNAme predictive model using XGBoost, which integrates the output of Megalodon, Nanopolish, and Deepsignal for analyzing data obtained using Oxford Nanopore Technologies (ONT). The consensus model enhanced DNAme detection at single-base resolution by 12% (mean square error) and improved accuracy at single-molecule resolution by 3% (F1-score accuracy) for human B-lymphocyte cell lines (NA12878 and NA19240). The consensus model also detected ∼200,000 more CpGs than Nanopolish. Combing variant calling and long-read phasing, NANOME can detect haplotype-aware allele-specific DNAme in known imprinting controls. We conducted haplotype-aware methylation detection on the T2T genome for dataset NA12878, revealing significant variations in DMR density between gap and non-gap regions, with notable higher densities in gap regions of chromosomes 2, 10, and 20. Overall, NANOME represents a significant step forward in DNAme detection and long-range epigenetic phasing, offering a robust and accessible tool for researchers studying the epigenome. Citation Format: Yang Liu, Ziwei Pan, Christina Chatzipantsiou, Emma Wade, Thatcher Slocum, Lasya Karuturi, Yue Zhao, Shilpita Karmakar, Sheng Li. NANOME: A Nextflow pipeline for haplotype-aware allele-specific consensus DNA methylation detection by nanopore long-read sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr LB345.