Constantin Ahlmann-Eltze (@const-ae.bsky.social)
@const_ae
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Postdoc at UCL with @JL_Reading. Previously at EMBL working with @wolfgangkhuber. Biostats, R, cancer immunology Find me on 🦋 at https://t.co/qOh57AUB49
London
Joined December 2010
@NadigAjay Thanks :) I discussed the idea a bit in However, such a test would require some additional statistical groundwork. I would love it if someone picked this up :)
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RT @clintomics: New single-cell analysis framework, LEMUR, disentangles covariates and latent cell states from multi-condition data to pred…
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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.
After 4y in the making, I am super excited that my main PhD project is published 🎉🥳🎉🎉🥳 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⬇️
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Big shout out to everyone involved: my supervisor @wolfgangkhuber and everyone else who helped along the journey: @OliverStegle @s_anders_m @zauggj @LSaund11 And lastly, this link should work even without a Nature subscription:
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RT @amleppa: Extremely proud to see my PhD project exploring intra-tumor heterogeneity in complex karyotype AML finally out in @NatureGenet…
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RT @hadleywickham: The #rstats community on bluesky seems to be really picking up steam, so you can also find me over there:
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@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 :)
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Great thread by Anshul, one of the pioneers of deep learning for biology, summarizing our preprint!
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@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.
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