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Cracking the regulatory code: We have genomes for 1000s of species, but ENCODE only for 2 – what do we do? Natural language models have shown that syntax and semantics can be learned from text alone. Can we do the same for genomes?⬇️ biorxiv.org/content/10.110…

Is binarization of scATAC-seq data necessary?Quantitative modeling of scATAC-seq data performs better at latent space learning and at the same time preserves quantitative information of accessibility. Join my talk at #ISMBECCB2023 Tue at 14:50 & Poster B98! HiTSeq 2024

Thrilled that our preprint describing our participation in the “SickKids clinical genomes and transcriptomes” CAGI challenge is now out in Research Square! researchsquare.com/article/rs-340…. One of the winning solutions of the challenge! #Transcriptomics #Genomics

Honored to have been granted by the ERC for our Synergy project EPIC with Kevin Verstrepen Kevin Verstrepen & Vicente Pelechano Pelechano lab! We aim for a breakthrough in cracking the regulatory code by combining omics, AI & synthetic biology. More here: shorturl.at/iDEHR

Wanna do Rare Variant Association Testing powered by deep learning? See Brian Clarke & my poster PB4113 Fr. 3pm on DeepRVAT. New results on phenome-wide application, binary traits, 10x faster than SOTA Oliver Stegle & gagneurlab collab. Update: shorturl.at/egtB0 #ASHG23

Come and join the Gagneurlab! Feel free reach out to me to get more insights into our work and lab culture as well as the great MUDS program!

Is binarization of scATAC-seq data really necessary? The conclusion from our analysis is that a quantitative treatment is in fact beneficial. Now out in Nature Methods! gagneurlab Fabian Theis nature.com/articles/s4159… Many additions since the preprint 👇(1/n)

Really enjoyed presenting our work on Deep Rare Variant Association Testing (DeepRVAT) today at #EESAIBio. Come and talk to us if you’re around want to learn more!

Excited to attend #eshg2024 with an ESHG fellowship! Presenting recent advances in DeepRVAT, now integrated with REGENIE for analysing diverse ancestries and low-prevalence traits using the full UKBB WES dataset. Catch my poster (P16.003) on Sat 3:45pm! gagneurlab Stegle Lab

Feeling extremely honored to receive the #eshg2024 Early Career Poster Award! This work wouldn’t be possible without everybody involved in DeepRVAT, esp. Brian Clarke gagneurlab Stegle Lab

Exciting to see DeepRVAT gene impairment scores integrated with gene functional representations to boost genotype-to-phenotype modeling. Very happy to have contributed to this project!

Excited to present “scooby”, which models multi-omic profiles (scRNA-seq coverage & scATAC-seq insertions) directly from 500 kb DNA sequence at single-cell resolution. This was a fantastic collaboration co-led with Johannes Hingerl. biorxiv.org/content/10.110…

Our paper on using machine learning to predict the impact of rare genetic variants is out! #DeepRVAT utilizes a fully data-driven approach to analyze annotated variants. DKFZ press release: dkfz.de/en/presse/pres……Publication in Nature Genetics: nature.com/articles/s4158…

Want to hear about how DeepRVAT gene impairment scores can be integrated with gene functional representations to boost phenotype prediction and rare variant association testing? Find out at Shubhankar's talk today if you're at #ASHG2024