Luca DENTI

"I know that I know nothing" (Socrates)

ASVA-CGR

Algorithms for Structural Variation Analysis in Challenging Genomic Regions

Funded under the “HORIZON.4.1 - Widening participation and spreading excellence” programme.

Grant agreement ID: 101180581

Funding scheme: HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships.

https://doi.org/10.3030/101180581

Outcomes

The project aimed to design algorithms and develop software tools to facilitate and improve genomic analyses of structural variations from sequencing datasets. It focused on two main scientific themes: structural variations and pangenomics.

Structural Variations

Accurate characterization of structural variations (genomic rearrangements affecting large DNA segments) plays a key role in unveiling their effects on human health, including their links with genetic diseases and tumors. Accordingly, our work pursued two complementary objectives: (i) an investigation of current best practices, along with their limitations, for benchmarking SV callers and (ii) the development of a new software tool for the discovery of somatic structural variations.

Pangenomics

In parallel, we investigated how pangenomics can help us achieve our goal of characterizing structural variations. Since pangenomics is an emerging research field, we first established the algorithmic foundation and focused on designing data structures and algorithms that enable the practical use of pangenome graphs within existing genomic analysis pipelines. These developments will facilitate the analyses and interpretation of structural variations.

Additional results

Over the course of the project, we also collaborated with other researchers on detecting differences between sequencing datasets, clustering third-generation transcriptomic datasets, and indexing massive bacterial databases.

Publications

  1. D. Andrukhovskyi, M. Madzin, L. Denti, T. Vinař, B. Brejová
    Efficient Algorithms for Pangenome Personalization
    WABI Proceedings (2026)

  2. A. Petescia, L. Denti, A. Gafurov, V. Hodorova, J. Nosek, B. Brejova, T. Vinar
    Alignment-free Detection of Differences Between Sequencing Data Sets
    iScience (2025)

  3. D. Cozzi, B. Riccardi, L. Denti, S. Ciccolella, K. Sadakane, P. Bonizzoni
    Pangenome Graph Indexing via the Multidollar-BWT
    SEA Proceedings (2025)

  4. L. Denti, Y. Shibuya
    Weighted de novo clustering of third-generation transcriptomic datasets
    ITAT Proceedings (2025)

  5. L. Denti, P. Bonizzoni, B. Brejova, R. Chikhi, T. Krannich, T. Vinar, F. Hormozdiari
    Pangenome graph augmentation from unassembled long reads
    bioRxiv (2025)

  6. L. Denti, T. Krannich, T. Vinar, R. Chikhi, P. Bonizzoni, B. Brejova, F. Hormozdiari
    Anyone can be the best: Impact of diverse methodologies on the evaluation of structural variant callers
    bioRxiv (2025)

  7. S. Ciccolella, D. Cozzi, G. Della Vedova, S. Kuria, P. Bonizzoni, L. Denti
    Differential quantification of alternative splicing events on spliced pangenome graphs
    PLOS Computational Biology (2024)

Software

Slides and Posters

Invited talks:

Talks:

Posters: