Sorry for the first figure, got a problem of background, here it is:

Tests show that:
1/ SNooPy has the best recall in our tests
2/ Using genomic long-read SNP callers does not (always) work well: most tools have very low recall, but DeepVariant perform much better than other tested methods
3/ The recall of all tools is still far from 100%

Preprint out! Check out our new long-read metagenomic SNP-caller, SNooPy 😀. Work with Chris Quince. Thread 🧵
👉 www.biorxiv.org/content/10.6...

🧵5/6
The sketching makes assembly extremely fast: a gut metagenome sample of 138Gbp of sequencing data was assembled in less that 2h and 10G RAM on 8 threads ⚡. And thanks to MSRs, *highly similar strains are not collapsed*

🧵3/ 6
MSRs have been defined by @lblassel.bsky.social @rayanchikhi.bsky.social and @pashadag.bsky.social in pmc.ncbi.nlm.nih.gov/articles/PMC....
Take a sequence, a value of k, and stream all k-mers through a function that output either a base or the empty character, and you got your sketch

So glad to have participated in #DSB2025, what a great workshop! For some mysterious reason it was the first time I attended after 3 years of sequence research. Thanks to all participants & organizers 😃

So glad to have successfully defended my Ph.D. last week 😀 Work on producing haplotype-resolved metagenomic assemblies using noisy long reads (HairSplitter) and high-fidelity long reads (Alice assembler, unpublished yet).
Thanks to my advisors Dominique Lavenier and Jean-François Flot ❤️