Gregor Sturm

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📣 Mark your calendars! The 2025 edition of the scverse conference will take place on 17-19 November at Stanford University (US) scverse.org/conference20...

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Just released a new version of the @scverse.bsky.social cookiecutter template: github.com/scverse/cook...

Some highlights:
🔃 improved template sync (merge conflicts now show up as such)
🚀 use hatch as project manager
🔧 lots of fixes and documentation updates

rogue-scholar.org

Nice post!
How did you generate the doi-link for a blog post?

LEMUR simplified | const-ae A simplified implementation of the LEMUR algorithm.

Blog post by @const-ae.bsky.social with a simple explanation of the manifold regression algorithm & code that underlies our paper “Analysis of multi-condition single-cell data with latent embedding multivariate regression” (doi.org/10.1002/eji....).

const-ae.name/post/2025-01...

Working with >1M cells Scirpy scales to millions of cells on a single workstation. This page is a work-in-progess collection with advice how to work with large datasets. Distance metrics: Computing pairwise sequence dist...

Just released scirpy v0.21 -- Now with GPU Support for Hamming sequence distance and a brand new tutorial for working with scTCR datasets >1M cells: scirpy.scverse.org/en/latest/tu...
@scverse.bsky.social

Release notes Version 1.11: 1.11.0 2025-02-14: Release candidates: rc2 2025-01-24, rc1 2024-12-20. Features: rc1 sample() supports both upsampling and downsampling of observations and variables. subsample() is n...

🎉 Scanpy 1.11.0 is out! 🎉 just after reaching 2000 stars on GitHub!

- sc.pp.sample replaces subsample with many new features
- Sparse Dask support pca
- session-info2 package for more reproducible notebooks

See the release notes:

Been looking forward to this talk since @alexpeltzer.bsky.social told me about DSO in October!

GitHub - Boehringer-Ingelheim/dso: Data Science Operations (dso) command line tool Data Science Operations (dso) command line tool. Contribute to Boehringer-Ingelheim/dso development by creating an account on GitHub.

I'd like to share DSO, a command line helper to build reproducible data science projects with ease.

It is an opinionated way to organize data science projects, built around data version control (DVC).

github.com/Boehringer-I...

We try to avoid that by using this with preprocessed data only. All the heavy lifting is done with nextflow pipelines before. Datasets up to tens of GBs have worked well so far.

Finally, many thanks to my colleagues @alexpeltzer.bsky.social, Daniel Schreyer and Tom Schwarzl for testing, adopting, and contributing to DSO.

Bytesize: data science operations (DSO) Gregor Sturm, Boehringer Ingelheim

If you want to learn more, I'll be presenting this at a @nf-co.re bytesize talk: nf-co.re/events/2025/...

We built this at @boehringerglobal.bsky.social to meet the quality standards required for biomarker analysis in clinical trials.

But I think this is useful for any kind of data analysis project.

An exemplary PCA plot with a "preliminary" watermark.

One of my favorite features: automated watermarking of all plots in a quarto report. Nobody gonna publish my plots anymore before I think they are ready.

It brings together the best tools:
- git, for code versioning
- dvc, for data versioning and tracking inputs and outputs
- jinja2, for templates
- uv, for Python dep mgmt
- quarto, for authoring reports
- hiyapyco, for hierarchical YAML config
- pre-commit, for linting

GitHub - Boehringer-Ingelheim/dso: Data Science Operations (dso) command line tool Data Science Operations (dso) command line tool. Contribute to Boehringer-Ingelheim/dso development by creating an account on GitHub.

I'd like to share DSO, a command line helper to build reproducible data science projects with ease.

It is an opinionated way to organize data science projects, built around data version control (DVC).

github.com/Boehringer-I...

We (Chen Zhan!) just launched #sccomp for #Python!

Testing for differences in cell-type proportion in #singlecell #spatial data?

#sccomp is a mixed-effect Bayesian model
- Use sum-constrained BetaBinomial distribution
- Outliers detect.
- Remove unwanted effects

github.com/MangiolaLabo...

GitHub - icbi-lab/luca: Single-cell Lung Cancer Atlas with 1.2M cells Single-cell Lung Cancer Atlas with 1.2M cells. Contribute to icbi-lab/luca development by creating an account on GitHub.

(2) Finding the mistake, tracing it back to its origin, and fixing it was only possible because the data and scripts for building the atlas are publicly available and fully reproducible. github.com/icbi-lab/luca

(1) Maintaining a data resource is very much like maintaining software. It is never "done" but constantly improving.

Cellxgene Data Portal Find, download, and visually explore curated and standardized single cell datasets.

Two years after publication of our single-cell lung cancer atlas, a user found a mistake in the annotation of the EGFR-status of some patients. We fixed the issue and the atlas is now updated on cell-x-gene: cellxgene.cziscience.com/collections/...

What are the takeaways from that? (1/3)

Scverse x Owkin Hackathon in Paris We're pleased to announce the next Scverse Hackathon will take place in the Owkin offices in Paris from 17/03/2025 9am to 19/03/2025 1:30pm. This hackathon is a joint initiative between the scverse c...

I am Stoked about our upcoming @scverse.bsky.social
and @owkin.bsky.social hackathon, focused on spatial omics data analysis.
📅 March 17-19, 2025
📍 Owkin office, Paris

Apply now: docs.google.com/forms/d/e/1F...

protein sequencing 👀

Overview of the LEMUR steps: (1) subspace alignment, (2) differential expression, (3) DE neighborhoods, (4) pseudobulking.

After 4y in the making, I am super excited that my main PhD project is published 🎉🥳🎉🎉🥳

www.nature.com/articles/s41...

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⬇️

The big issue here in Germany is that we pay ~20 ct/kWh in fixed network fees and tax. Really limits how much you can save.

While definitely interesting, dynamic tariffs have a much higher cost-saving potential for devices that consume a lot of energy and are easy to regulate automatically. Such as a heat pump or electric car - of which we have neither, for now.

There's a certain price risk, though. In the energy crisis 2021-2022 prices increased significantly. However prices in 2023 were down to normal, while many fixed price tariffs increased their rates.

Monthly comparison of fixed price tariff (AÜW) with dynamic tariff (tado).

Dynamic electricity tariffs are an incentive to use energy when it's abundant and emits little CO2.

But are they also cheaper?

✅ For 2024, we would have saved 10-13% compared to our current fixed price tariff. Without any optimization.

Full post (in German): grst.github.io/dynamischer-...

Modern tar detects the compression automatically when reading from a file. So `tar xvf` covers most of the cases already.

To bring to light data science topics that usually don’t make it into publications I started a blog on this topic: hrovatin.github.io By interviewing different researchers, I plan to find out what is going on in the community.