Discover and read the best of Twitter Threads about #SpatialOmics
Most recents (4)
1/15 🧵 I'm thrilled to share the fantastic news that our Pan-Cancer T cell Atlas is now live @NatureMedicine nature.com/articles/s4159… @MDAndersonNews #SingleCell #SpatialOmics #TumorMicroenvironment #CancerImmunotherapy
2/15 🧵Our team has created a pan-cancer single-cell T cell atlas that integrates 27 scRNA sequencing datasets, including 9 unique datasets from @MDAndersonNews, covering 16 cancer types. It presents the most detailed picture to date of the heterogeneity of T cells within the TME
3/15 🧵We defined 32 T cell states in this study, and further identified 7 subpopulations within the CD4+ Treg subset, 5 within the CD4+ Tfh population, and 8 states among proliferating T cells.
Some thoughts on the Nooma Bio insights from @new299 's substack blogpost:
I saw this picture and it reminded me a lot of another similar schematic, which is for photolithography of semiconductor chips (right-hand picture)
I saw this picture and it reminded me a lot of another similar schematic, which is for photolithography of semiconductor chips (right-hand picture)
The whole point of the more complicated setup in the Nooma Bio approach is that, by having 3 electrodes and two pores, one can control the flow better. But also, read the same single molecule more than once in the same pore pair. Nava puts it clearly here:
Further down, it seems there would be a limit to how fast/slow the molecules go through the pore, which would make it difficult to reach DNA base resolution (even worse for #NGPS protein sequencing)
My highlights of the @10xGenomics #Xperience2021 event. The list of products keeps growing, I would highlight Chromium Connect as an underappreciated tool to bring the products up another level of throughput. Important as with #NGS, it won't take long to go from n=1 to n=96+.
#CellPlex species-agnostic multiplexing up to 12 samples: not dissimilar to products such as TotalSeq, but baked-in so that it's been tested to work with the rest of the workflow.
Going close to 1M cells, the #ChromiumX brings about 100x fold throughput increase, all marked with 'HT' in the Kits. I'd be interesting to know how the different #BodyAtlas projects embrace this and for what.
Excited to release the first preprint from my lab: a new framework to convert existing NGS tube-reactions into spatial techniques using compressed sensing principles and a probabilistic algorithm that we call #Tomographer biorxiv.org/cgi/content/sh…
In the lab we are thrilled about possibilities offered by #spatialomics methods, and a bit impatient... it will take a bit until methods for the different omics are available. That's when we had the idea of using already available low-input protocols to obtain spatial information
The core idea is sampling a tissue by cutting thin slices at several orientations so as to obtain a high throughput readout from each of the strips. The measurements are then used to reconstruct the original localization of the signal by a maximum a posteriori estimation
