🚀 Hevelion, une start-up issue de @fbm-unil.bsky.social @unil.bsky.social, développe un outil «omique» pour la #cartographie des cellules et de leurs interactions, notamment en #oncologie.
Lire la rencontre avec son fondateur @marcovarrone.bsky.social
🔗 www.unil.ch/news/fr/1763...
#SpatialOmics
I collected all of what I could find about the upcoming Illumina Spatial Transcriptomics technology, with some predictions about costs and sensitivity compared to 10x Genomics Visium HD
www.batcheffect.com/p/the-giant-...
Great work @grst.bsky.social ! I remember there were some differences between DESeq2 (R) and pyDESeq2 (Python).
Do you think it's safe to assume that pyDESeq2 is also the best approach for the simple case? :)
And for anyone who has considered contributing to an open source package: don't be scared to propose changes.
Even if it's not a complete and perfect solution, whoever is maintaining the package will help you in get to the right solution and they will be incredibly grateful.
For people like me who don't have a team behind a package like CellCharter, contributions like these mean a lot. So thank you Lukas :)
And congratulations, it's not always easy to jump into an existing codebase and propose changes.
RCS measures how large a cell niche (aka spatial domain aka spatial cluster) is compared to what would be normally expected.
This pushed me to completely rewrite the system for generating and plotting boundaries for cell niches.
The new system is now more efficient, consistent, and visually clear.
A few weeks ago, we released CellCharter v0.3.5.
Among some bug fixes, we received our first contribution from an external contributor: @loggas.bsky.social !
He designed a new metric called Relative Component Size (RCS).
After 6 (healthy) months of hiatus from social media, first post with a brand new conference announcement!! 🔥COMPUTATIONAL BIOLOGY IS EVERYWHERE! Join us in Lausanne for the first international Computational Biology Symposium! 18-19 September 2025 Registrations are OPEN! cbiosymposium.unil.ch
By the way, here in Switzerland the public defense is meant for the general public, so the presentation is understandable by anyone, and I even sneaked some jokes inside.
Last year I completed my PhD and my father recorded my public defense 📹
So I decided to share it!
I talked about the communities of cells in our bodies and how we develop algorithms to study them.
Hope you enjoy it!
The only sort of gatekeeper I wish we saw more of were those who wanted better software. Who cares if your model performs the best if it's unusable, or if your pipeline aligs reads faster if it only works on your local work computer? Or if there's no documentation on how to use any of it.
The scverse ecosystem is one of the best things that could have ever happened to the single-cell and spatial fields.
Smoother computational analyses mean faster and better research
Contributing to this project has been very cool!
Quick tip for anyone interested in cell segmentation: I started with StarDist but it failed to detect nuclei in samples with regions of very different cell density.
Switched to DeepCell Mesmer and it worked like a charm!
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.
3. How spatial omics can identify cell communities and true cell interactions to understand what is really happening.
4. How discoveries driven by spatial omics will lead to new effective therapies.
1. How two types of cells, fibroblasts and macrophages, can cooperate to support cancer.
2. Why some of the therapies targeting only one of those cell types failed in clinical trials.
We are used to thinking that, when an organism has cancer, all other cells will fight it.
We are now realizing that this is not true, and some of these cells may even help it.
In the fourth Batch Effect post I talked about 4 aspects:
🔬 Spatial omics: revolutionary breakthrough or just incremental progress?
In the third Batch Effect blog post, I compared this emerging technology to the historic hype around interferon therapy.
Is this time going to be different?
www.batcheffect.com/p/breakthrou...
What do fruit pies 🥧, lego sets🧩, and cities🏙️ have in common?
They are all metaphors used to describe spatial transcriptomics.
In the second Batch Effect blog post I explored the best metaphor to make anyone understand what is spatial transcriptomics
www.batcheffect.com/p/the-best-m...
Bonus tip: if you are considering creating a package to be included within the scverse ecosystem, the cookiecutter template already sets up 5 of the 8 mandatory requirements.
A common problem with templates and frameworks is that they tend to restrict what you can do to keep you consistent.
But this is not the case here.
I used the scverse template even for projects that are not strictly related to single-cell or computational biology.
It sets up beautiful documentation generated directly from your code like in the picture.
Finally, it gives automatic actions for publishing and updating the package.
Every time you push code to your main GitHub branch, scverse’s cookiecutter automatically runs tests.
Even better, it supports testing with pre-release dependencies!
This means you can detect breaking changes in upcoming dependency updates before they're officially released.
If you are considering creating a Python package I strongly suggest cookiecutter-scverse by @scverse.bsky.social
It’s a template that already incorporates many useful features.
github.com/scverse/cook...
Same as what was said about React, Vue may be a bit overkill unless you want 100% customization.
But if you are interested or you want to use it as an excuse to learn Vue.js, there is also an official project called VuePress that is focused on showing content using Markdown
You mean installing VS Code? It should be much easier than something like the Linux subsystem.
You just need to download the VS Code file and click install
I do! I find it not that different from JupyterLab.
It's just nice to have everything in one place since I tend to mix scripts with notebooks.
The Human Cell Atlas: towards a first draft atlas.
I often read people complaining about "yet another atlas" published, but they are an important component of modern cell biology.
They drive discovery, enable reproducibility, and I use them in nearly every project I work on.
A few months ago, I started Batch Effect, a blog on the latest in cancer research under the lens of computational biology and spatial omics.
I never shared here, so I'll start posting one old article every week.
Hopefully we'll catch up just in time for a new series I am working on!
Lastly, big thanks to Lukas Hatscher for spotting a memory leak in the differential neighborhood enrichment function!
This pushed me to refactor it completely.
Now it's much faster and more memory-efficient. 🚀 4/4
