Constantin Ahlmann-Eltze (@const-ae.bsky.social) @const_ae
Postdoc at UCL with @JL_Reading. Previously at EMBL working with @wolfgangkhuber. Biostats, R, cancer immunology Find me on 🦋 at https://t.co/qOh57AUB49 github.com/const-ae London Joined December 2010-
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@NadigAjay Thanks :) I discussed the idea a bit in github.com/const-ae/lemur… However, such a test would require some additional statistical groundwork. I would love it if someone picked this up :)
After 4y in the making, I am super excited that my main PhD project is published 🎉🥳🎉🎉🥳 nature.com/articles/s4158… LEMUR is a tool to analyze multi-condition single-cell data and model differential expression as a continuous function of the cell-state space. Some highlights⬇️
New single-cell analysis framework, LEMUR, disentangles covariates and latent cell states from multi-condition data to predict counterfactual gene expression and identify cell neighborhoods with similar DEGs without clustering. doi.org/10.1038/s41588… @NatureGenet @wolfgangkhuber
For the Monday morning crowds :) Also, take a look at my blog post, in which I compress the full lemur package into 100 lines of code and explain the core algorithm. const-ae.name/post/2025-01-0…
After 4y in the making, I am super excited that my main PhD project is published 🎉🥳🎉🎉🥳 nature.com/articles/s4158… LEMUR is a tool to analyze multi-condition single-cell data and model differential expression as a continuous function of the cell-state space. Some highlights⬇️
Big shout out to everyone involved: my supervisor @wolfgangkhuber and everyone else who helped along the journey: @OliverStegle @s_anders_m @zauggj @LSaund11 bsky.app/profile/ronnyb… And lastly, this link should work even without a Nature subscription: rdcu.be/d5puu
Finally, we demonstrate LEMURs usefulness on - a treatment vs. ctrl dataset from glioblastoma, - Zebrafish developmental time course, and - a spatially resolved Alzheimer dataset where we find intriguing DE patterns
Extremely proud to see my PhD project exploring intra-tumor heterogeneity in complex karyotype AML finally out in @NatureGenet ! 🎉👩🏻🔬 They say that 10,000 hours make you an expert, so I guess after more than five years of work I’m half-way there 😅 ⬇️1/5 nature.com/articles/s4158…
The #rstats community on bluesky seems to be really picking up steam, so you can also find me over there: bsky.app/profile/hadley…
@kasparmartens Very nice work. I like your mean-perturbation-effect baseline, and the LLM embeddings from the sequence and text are a cool idea. I will update the Discussion to incorporate this :)
There's a lot of excitement about foundation models and their ability to learn biology 🧬💻 But current tools for perturbation prediction perform worse than simple linear models! We need more careful benchmarking to make progress. biorxiv.org/content/10.110…
🚀Interested in doing a PostDoc in my lab? Consider applying for a🇨🇭SNSF Swiss Postdoctoral Fellowship 2024. If you have any questions, join the information event tomorrow via Zoom (register via shorturl.at/zP93m) or reach out to us via bunnelab.com! 🧬Who should apply? Check that you fulfill the requirements. And: We are in particular interested in candidates with background in computational biology or machine learning applied to the biomedical domain!
📢 #Call for SNSF Swiss Postdoctoral Fellowships 2024 This highly competitive call is aimed at researchers who wish to obtain a position in a non-profit research institution in Switzerland for a period of 12 to 24 months. 🗓️Deadline: 2 December 2024 sohub.io/6afa
@science_wallet That sounds exciting, can't wait to see what you are cooking up :)
Great thread by Anshul, one of the pioneers of deep learning for biology, summarizing our preprint!
biorxiv.org/content/10.110… Nice benchmark of single cell "foundation models" (scGPT, scFoundation) and GEARS (a GNN model) further hyped as "virtual cell models" against linear baselines on perturbation prediction. Long-story short: they can't beat the linear baselines. 1/
@pan_cancer @Alejandro__TL replied on Github and clarified that Prophet in its current form is not intended for predicting perturb-seq experiments, but that they are considering adding that feature in the future.
@pan_cancer Yes, it would be great to include Prophet in the benchmark. I just asked how to best apply the software to genetic perturbation data (github.com/theislab/proph…) because I don't quite understand yet how to use the software :)
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