Machine Learning for spatial omics.
https://batcheffect.com
CellCharter is a computational framework to identify and study cellular niches in large-scale spatial transcriptomics, proteomics, and even epigenomics data.
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).
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).
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!
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!
Smoother computational analyses mean faster and better research
Smoother computational analyses mean faster and better research
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!
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!
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:
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:
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...
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...
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...
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...
It’s a template that already incorporates many useful features.
github.com/scverse/cook...
It’s a template that already incorporates many useful features.
github.com/scverse/cook...
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.
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.
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!
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!
- Now part of the Scverse ecosystem
- More efficient differential neighborhood enrichment
- Peak finding for cluster stability
- Compatible with the latest PyTorch
A few lessons learned along the way 🧵 1/4
github.com/CSOgroup/cel...
- Now part of the Scverse ecosystem
- More efficient differential neighborhood enrichment
- Peak finding for cluster stability
- Compatible with the latest PyTorch
A few lessons learned along the way 🧵 1/4
github.com/CSOgroup/cel...
CellCharter is a computational framework to identify and study cellular niches in large-scale spatial transcriptomics, proteomics, and even epigenomics data.
CellCharter is a computational framework to identify and study cellular niches in large-scale spatial transcriptomics, proteomics, and even epigenomics data.
I have learned a lot about it in the last 3 years and I would love to share it, but I still don't know in which format (posts, blogs or videos).
I have learned a lot about it in the last 3 years and I would love to share it, but I still don't know in which format (posts, blogs or videos).