Svirlpool: structural variant detection from long read sequencing by local assembly

Motivation: Long-Read Sequencing (LRS), and Oxford Nanopore Technologies (ONT) in particular, has greatly improved the detection of structural genome variants (SVs). Fast alignment-based ONT callers achieve strong benchmark performance, but they necessarily reduce the read sequence to alignment-derived signals when deciding whether variants are shared across samples. This can be limiting for cohort and clinical analyses, especially for insertions and repeat regions where sequence representation matters. We present Svirlpool, a multi-sample SV caller for ONT data that builds local consensus assemblies of candidate SV regions and retains the assembled sequence up to the final joint-calling ste