Vizitig: context-rich exploration of sequencing datasets

Recent advances in k-mer indexing have facilitated the cataloging and rapid querying of planetary-scale genomic data. While these indices excel at high-throughput sequence lookups, they often lack context-rich exploration capabilities and rely on simplistic match-based queries. This gap hinders deeper investigations into variants, regulatory elements, and other features crucial for pangenomic and transcriptomic analyses. We present Vizitig, a novel system that harnesses a de Bruijn graph as the core data structure. By directly encoding overlapping k-mers from both genome and transcriptome data, Vizitig supports the processing of partially or completely unassembled sequences, making it broadly applicable from collections of genomes to eukaryotic RNA-seq. Vizitig integrates k-mer indices into a database framework, providing an intuitive, metadata-aware approach to querying. Users can select candidate regions by specific annotations (e.g., genes, motifs) or sample-specific features (e.g., abundance, presence or absence in annotated gene or a sample), retrieving relevant graph neighborhoods and associated meta-data from extensive datasets.