GIN-TONIC: Non-hierarchical full-text indexing for graph-genomes

Öztürk, U.; Mattavelli, M.; Ribeca, P.

doi:10.1101/2023.11.01.565214

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bioRxiv · 10.1101/2023.11.01.565214

GIN-TONIC: Non-hierarchical full-text indexing for graph-genomes

Öztürk, U.·Mattavelli, M.·Ribeca, P.

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Abstract

This paper presents a new data structure, GIN-TONIC, designed to index arbitrary string-labelled directed graphs representing, for instance, pangenomes or transcriptomes. GIN-TONIC provides several capabilities not offered by other graph-indexing methods based on the FM-index. It is non-hierarchical, handling a graph as a single monolithic object; it indexes at nucleotide resolution all possible walks in the graph without the need to explicitly store them; it supports exact substring queries in polynomial time and space for all possible walk roots in the graph, even if there are exponentially many walks corresponding to such roots. Specific ad-hoc optimisations, such as a precomputed cache, allow GIN-TONIC to achieve excellent performance for input graphs of various topologies and sizes. Robust scalability capabilities and a querying performance close to that of a linear FM-Index are demonstrated for two real-world applications, a human pangenome and transcriptome. Source code and associated benchmarks are available on GitHub. Availability and implementationGIN-TONIC and all related programs are available at https://github.com/uensalo/gin.

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Öztürk, U., Mattavelli, M., Ribeca, P.. 2023-11-04. GIN-TONIC: Non-hierarchical full-text indexing for graph-genomes. https://doi.org/10.1101/2023.11.01.565214

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