Luca Denti

Postdoc @unimib
Computer Scientist with a passion for Bioinformatics

[RECOMB Conference Series @RECOMBconf]

Morning! Let's start the day! SVDSS: structural variation discovery in hard-to-call genomic regions using sample-specific strings from accurate long reads by Luca Denti. #RECOMB2023

[PANGAIA Project @PangaiaProject]

Talk from @BonizzoniPaola starting the #ShonanMeetingPangenomics

[Nature Methods @naturemethods]

SVDSS combines multiple strategies to improve detection of structural variation using low-error long-read sequencing data. @l_denti @ParsoaKhorsand @DavisCompGen @BonizzoniPaola @PangaiaProject @RayanChikhi
https://t.co/EY2znczRBb

[Luca Denti @l_denti]

Code is freely available at https://t.co/eHad6JJHpL

[Luca Denti @l_denti]

Our work on Structural Variations discovery from accurate long reads (@PacBio HiFi) is out (https://t.co/EmfM2xunJo). Joint work with @l_denti @ParsoaKhorsand @BonizzoniPaola @RayanChikhi @DavisCompGen

[Luca Denti @l_denti]

For now SVDSS can be used to discover insertions and deletions. We have plans to extend its functionalities to other SVs, such as inversions and translocations. Other extensions include somatic SVs discovery and SVs genotyping.

[bioRxiv Bioinfo @biorxiv_bioinfo]

Pangenome Graph Construction from Genome Alignment with Minigraph-Cactus https://t.co/SIukrRJpTT #biorxiv_bioinfo

[Yoann Dufresne @yoann_dufresne]

In this new Bioinformatics Application Note, we introduce a file format named KFF for efficiently storing kmers on disk.
https://t.co/20gTzasFuD

[Yuri Pirola @YuriPirola]

First steps in #pangenomics? Check out our new tutorial!
https://t.co/VlOzRfuZzl
Thanks @jasmijnbaaijens Paola Bonizzoni Christina Boucher @giandellavedova Raffaella Rizzi @jltsiren @PangaiaProject

[Luca Denti @l_denti]

Code is freely available at https://t.co/AkyH4qfMGH

[Luca Denti @l_denti]

We have a new preprint out showing that k-mers can be replaced by variable-length strings for the analysis of long and accurate reads (e.g. HiFi)
https://t.co/uUJ1UtVCFC
Joint work with @KhorsandParsoa @BonizzoniPaola @RayanChikhi @DavisCompGen

[Luca Denti @l_denti]

SFS strings are more expensive to compute than k-mers. In the paper we introduce an heuristic algorithm that finds non-overlapping SFS strings efficiently.