DNA-m6A calling and integrated long-read epigenetic and genetic analysis with .

Long-read DNA sequencing has recently emerged as a powerful tool for studying both genetic and epigenetic architectures at single-molecule and single-nucleotide resolution. Long-read epigenetic studies encompass both the direct identification of native cytosine methylation and the identification of exogenously placed DNA -methyladenine (DNA-m6A). However, detecting DNA-m6A modifications using single-molecule sequencing, as well as coprocessing single-molecule genetic and epigenetic architectures, is limited by computational demands and a lack of supporting tools. Here, we introduce , a state-of-the-art toolkit that features a semisupervised convolutional neural network for fast and accurate identification of m6A-marked bases using Pacific Biosciences (PacBio) single-molecule long-read sequencing, as well as the coprocessing of long-read genetic and epigenetic data produced using either the PacBio or Oxford Nanopore Technologies (ONT) sequencing platforms. We demonstrate accurate DNA-m6A identification (>90% precision and recall) along >20 kb long DNA molecules with an ∼1000-fold improvement in speed. In addition, we demonstrate that can readily integrate genetic and epigenetic data at single-molecule resolution, including the seamless conversion between molecular and reference coordinate systems, allowing for accurate genetic and epigenetic analyses of long-read data within structurally and somatically variable genomic regions.