#Spatialtranscriptomics

Excited to share our latest study in Cardiovascular Research (@escardio)! 🎉 Using CosMx WTX #spatialtranscriptomics (@brukerspatial) and paired plaque-PBMC #scRNAseq, we reveal critical cellular drivers of plaque instability beyond stenosis severity.

Stoked to share our new paper w/ @TiroshLab in @NatureGenet! Using spatial multi-omics we characterized two distinct modes of p-EMT in HNSCC, each with their own distinct ecosystems and drivers. #SpatialTranscriptomics #HNSCC #Visium #CODEX #EMT

Excited to share our lab's new preprint led by Ting @huanting_ong introducing paired-surface spatial mechanomics! We link nanoindentation stiffness maps with #SpatialTranscriptomics to connect local tissue mechanics with molecular state. 🔗 🧵1/7

🧬 生信×AI日报 第012期｜10-27 空间组学不只问细胞在哪——Nat BME 的 SPACER 在 37 套 SRT 上把招募信号抬到 4–21×。🧵 #SpatialTranscriptomics #Bioinformatics

#SpatialTranscriptomics #ThoracicAorticDisease Human aorta is a mm-thick layered organ (50~60 circumferential Elastic-contractile units in adult) Its lumen & adventitia sides receive different chemical/mechanical inputs Any phenotypic/signaling gradients of #SmoothMuscleCells across the aortic medial depth?😆👇 Here is a very cool & informative study from one of my most favorite scientists, Dr. Hiromi Yanagisawa @HYanagisawaLab 👏 Micro-biopsies RNAseq from 4 distinct layers in human aortic media 5 #BicuspidAorticValue + 4 Sporadic Extracellular Matrix signaling (FN1/VCAN/MGP/POSTN) enriched in innermost layer (Beautiful POSTN IHC😍) TGFβ BAV > Sporadic Inflamm Sporadic > BAV Mechanosensing in innermost layer Sporadic > BAV🥸 #AortaEd #JVSVS 2026 @JVascSurg

I love how #spatialtranscriptomics can map #transdifferentiation in the actual tissue. In our @NatureComms article we show the spatio-temporal trajectory of AT2 #progenitor cells to the AT1 cell type in an attempt of the #lung to repair the damage caused by the #COVID-19 disease.

Mapping isoforms and regulatory mechanisms from spatial transcriptomics data with SPLISOSM. #SpatialTranscriptomics #Isoforms @NatureBiotech

🧬 生信×AI日报 第011期｜10-26 空间分割换方法，下游细胞身份与配体受体推断会变——Nat Methods 评了 11 方法×15 数据（约 230 万细胞）。🧵 #SpatialTranscriptomics #Bioinformatics

DeepMAST: a multi-agent AI for spatial transcriptomics that analyzes data, retrieves evidence, and prioritizes targets Applied to lung fibrosis → nominated ICAM-1 incredible work by junghyun with Peter Chen, @moorejh #AgenticAI #spatialtranscriptomics

I am updating my lecture slides on #spatialtranscriptomics to use author names + remove journal names to de-emphasize brands and re-emphasize people per #HHMI recs. In the process, I realized ALL the seminal techdev work has been led by co-first authors contributing equally 🧵1/3

#SpatialTranscriptomics STcompare Test your gene of interest if it is differentially spatially patterned (r, p, s)🤠 Spatial correlation Spatial fold change Control for spatial autocorrelation Comparisons will be straightforward with Alignment (STalign) & Rasterization (SEraster) if you have structurally similar tissues across conditions (If not, could we convert the spatial coordinates to a relative distance from a landmark, e.g. villi tip, athero-lesion cap, meninge?😁) @kalen_clifton @JEFworks bioRxiv 2025

Spatial AI must read more than genes. SToFM learns tissue, neighborhood and gene-scale signals from 88M cells, with strong cross-slice results in segmentation and annotation. Full article: #SpatialTranscriptomics #AIforScience

#SpatialTranscriptomics Optimizing Xenium @10xGenomics In Situ data utility by quality assessment & best-practice analysis workflows If you are a Xenium user, this is a must-read🔥 👉Segmentation: Cellpose + Baysor (Segmentation-free alternative: SSAM, Points2Regions) 👉Preprocessing: Library size normalization, log-transformation, scaling, k-nearest neighbors graph (all PCs + 16 neighbors), Louvain clustering 👉Spatially variable feature selection: Squidpy Moran's I, Seurat Moran's I, Sinfonia, SomDE, Giotto, Hotspot 👉Imputation: SpaGE, Seurat, Tangram, SpaOTsc 👉Spatial domain identification: binning-based strategy, Bansky, SPACEL Performance vs CosMX, Molecular cartography, MERFISH, MERSCOPE, high-sensitivity ISS @naturemethods 2025

DeepSpaceDB >2k #SpatialTranscriptomics Visium samples 👉Interactive, downloadable data analysis QC➡️ manual/LLM image annotation➡️ in-sample or cross-sample spot clustering BASS BayesSpace➡️ Spatially variable genes singleCellHaystack SPARK-X binSpect➡️ Cell type deconvolution RCTD SPOTlight 👉Cross-sample/Cross-study comparison 👉Analyze your own data 👉Database-wide gene/pathway inquiry @alexisvdb #NucAcidRes 2026

Comparative analysis of commercial Imaging-based #SpatialTranscriptomics methods Xenium CosMx 1k MERSCOPE Tissue Microarray 17 tumors + 16 normal tissues Transcript count Corr. with reference bulk TCGA GTEx RNAseq or scRNAseq Segmentation (Precision Recall F1 score) Accuracy: Elongated < Sparse < Dense cells Cell type annotation 2024 CosMx @brukerspatial protocol (vs 2023)▶️ 10-fold ⬆️sensitivity!😮 MERSOPE sensitive to RNA quality @GoodsBrittany @NatureComms 2025

3D #SpatialTranscriptomics Whole cardiomyocyte in adult🐭🫀 10x 10 µm cryosections 3.5 µm BMKMANU S3000 ST chips WGA stain-Cellpose➡️cell boundary Dynamic time warping +Optimal transport +Centroid distance ➡️3D registration 2.7k genes/cell vs 10x VisiumHD, snRNAseq Intracellular RNA asymmetry Mito-metabolism at proximal end Neuronal-like signaling at distal end

🚨New #SpatialTranscriptomics #Bioinformatics data resource out in @naturemethods. SODB, a platform with &gt;2,400 manually curated spatial experiments from &gt;25 spatial omics technologies &amp; interactive analytical modules. This🧵will walk you through all the features of SODB [1/33]

Systematic comparisons among 4 subcellular-resolution #SpatialTranscriptomics methods Stereo-seq v1.3 Visium HD FFPE CosMx 6k Xenium 5k Human Tumors Ground truth CODEX, +scRNAseq Gene detection sensitivity (CosMx performance...🙁) (Spatial) false positives Transcript-protein correlation Cell segmentation Cell type annotation & spatial alignment to CODEX Spatial clustering Spatial pathway enrichment @NatureComms 2025

A guidebook of spatial transcriptomic technologies, data resources &amp; analysis approaches🤠 A great ending for my 2-wk learning of #SpatialTranscriptomics tools Start reading real-world #SpatialOmics &amp; preparing for @IVBM2024😆 @CSB_Journal 👉Jan 2023

Mapping the transcriptome: Realizing the full potential of spatial data analysis A must-read for #SpatialTranscriptomics beginners Learn from Geographical science #SpatialAutocorrelation #GeographicallyWeightedRegression @LZormpas @sjcockell Cell 2023