Joined December 2010
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Constantin Ahlmann-Eltze (@const-ae.bsky.social) retweeted
3 Jan 2025
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/s41588-024-0… @NatureGenet @wolfgangkhuber
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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.
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/s41588-0…
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⬇️
ALT Overview of the LEMUR steps: (1) subspace alignment, (2) differential expression, (3) DE neighborhoods, (4) pseudobulking.
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After 4y in the making, I am super excited that my main PhD project is published 🎉🥳🎉🎉🥳
nature.com/articles/s41588-0…
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⬇️
ALT Overview of the LEMUR steps: (1) subspace alignment, (2) differential expression, (3) DE neighborhoods, (4) pseudobulking.
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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
ALT Screenshot of the glioblastoma figure
ALT Screenshot of the Zebrafish figure
ALT Screenshot of the Alzheimer plaques figure
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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 bsky.app/profile/ronnybergma…
And lastly, this link should work even without a Nature subscription: rdcu.be/d5puu
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Constantin Ahlmann-Eltze (@const-ae.bsky.social) retweeted
25 Nov 2024
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/s41588-0…
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Constantin Ahlmann-Eltze (@const-ae.bsky.social) retweeted
29 Oct 2024
The #rstats community on bluesky seems to be really picking up steam, so you can also find me over there: bsky.app/profile/hadleywickh…
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Constantin Ahlmann-Eltze (@const-ae.bsky.social) retweeted
25 Sep 2024
🚀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!
2 Sep 2024
📢 #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
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Great thread by Anshul, one of the pioneers of deep learning for biology, summarizing our preprint!
21 Sep 2024
biorxiv.org/content/10.1101/…
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/
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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/10.1101/…
ALT Beeswarm plot of the double perturbation predictions. The Additive model outperforms GEARS, scGPT, and scFoundation by a large margin
ALT Line plot of the accuracy of the predictions that are most different from the additive model. The No Change model outperforms GEARS, scGPT, and scFoundation.
ALT Beeswarm plot of the single perturbation predictions. The linear model perform as good as GEARS, scGPT, and scFoundation.
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This is the result of my brief postdoc with @s_anders_m in the last 6 months and grew out of an intriguing reviewer comment for the LEMUR paper with @wolfgangkhuber.
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Very excited to announce that I started a postdoc in @JL_Reading's lab at UCL working on tumor immunology 🥳
So, if you are in London and want to meet for a coffee, hit me up :)
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Constantin Ahlmann-Eltze (@const-ae.bsky.social) retweeted
10 Sep 2024
Great talk from @const_ae this morning beautifully giving the intuition behind LEMUR, a computational tool for the analysis of multi-condition single-cell data! #AsconaSpatial2024
GitHub: github.com/const-ae/lemur
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I wrote a new ggplot2 extension to draw Bezier curves github.com/const-ae/ggbezier🎉
The curves are defined by a set of control points and the tangents at those points. This makes each parameter directly interpretable and the curves easy to tweak!
#rstats #ggplot2
ALT Screenshot of an example plot made with ggbezier
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