DIANA: An integrated pipeline for analysis of long-read whole-genome sequencing data for molecular neuropathology.

SummaryCentral nervous system (CNS) tumor diagnosis requires comprehensive genomic profiling including DNA-methylation classification, copy-number variants (CNV), gene fusion analysis, small variant detection and MGMT promoter methylation status. Long-read sequencing platforms such as nanopore sequencing by Oxford Nanopore Technologies and SMRTseq by PacBio can capture all these in a single assay, but integrating diverse analytical tools to leverage the advantages of long-read sequencing remains complex. We present DIANA (Diagnostic Integrated Analytics of Neoplastic Alterations), a pipeline providing fully automated end-to-end processing of long-read whole-genome sequencing data from aligned sequence reads. DIANA produces a human readable report that combines methylation classification with prioritized genetic variants to support CNS tumor diagnostics and clinical decision-making. Availability and implementationDIANA is an open-source Nextflow pipeline, freely available through Docker or Apptainer/Singularity technologies. The source code, comprehensive documentation, and installation protocols are available on GitHub: https://github.com/VilhelmMagnusLab/DIANA.git. Supplementary informationSupplementary data are available at Bioinformatics online.