CytoVI: Deep Generative Modeling of Antibody-Based Single Cell Technologies 1. The article introduces CytoVI, a probabilistic deep learning framework designed to integrate antibody-based single cell technologies like flow cytometry, mass cytometry, and CITE-seq. It effectively removes technical variation and embeds cells into a meaningful low-dimensional representation corresponding to a cell's intrinsic state. 2. CytoVI outperforms existing computational methods in handling integration scenarios. It can impute missing markers in experiments with overlapping antibody panels, impute a cell's transcriptome if paired with CITE-seq data, and facilitate the automated detection of cellular states associated with clinical covariates. 3. The model was applied to generate an integrated B cell maturation atlas across 350 proteins from smaller antibody panels measured by mass cytometry. It identified proteins associated with immunoglobulin class-switching in healthy humans. 4. Using a cohort of B cell non-Hodgkin lymphoma patients measured by flow cytometry, CytoVI uncovered T cell states associated with the disease. It also demonstrated robust performance for analyzing standard diagnostic flow cytometry antibody panels, enabling automated detection of tumor populations and diagnoses of incoming patient samples. 5. CytoVI is available as open-source software, leveraging advanced optimization strategies for scalable modeling of hundreds of millions of cells. It paves the way for a next generation of AI-powered cytometry integrated with other single cell genomic modalities, with great potential for biomarker discovery and clinical applications. 📜Paper: biorxiv.org/content/10.1101/… 💻Code: github.com/YosefLab/cytovi-r… #CytoVI #SingleCellTechnology #DeepLearning #Bioinformatics #Cytometry #AntibodyBased #Integration #BiomarkerDiscovery #ClinicalApplications

It was a pleasure to be part of the 3rd annual Single Cell and Spatial Biology symposium today along with a fantastic lineup of speakers and researchers in the field of #SingleCellMultiOmics. #SeyedasliLab #TumourHeterogenity #SingleCellTechnology

Following several kind requests, here is a high-level summary of our pre-print in @biorxivpreprint (doi: doi.org/10.1101/2024.10.03.6…): STAMP: Single-Cell Transcriptomics Analysis and Multimodal Profiling through Imaging STAMP is a scalable, cost-efficient method for single-cell transcriptomics and multimodal profiling through imaging. It bypasses sequencing, significantly reducing costs while enhancing throughput. #SingleCellRNA #SpatialOmics #STAMP The motivation for this paper comes from the limitations of current scRNA-seq methods, which are costly, inefficient, and struggle to capture low- and high-abundance transcripts. Challenges like droplet instability, cell damage, limited cell capture, cross-contamination, inefficient indexing, and high sequencing costs affect ultra-low and ultra-high cell profiling, hindering accurate analysis of complex cell populations. #Limitations #DropletMicrofluidics STAMP addresses these issues with a scalable, cost-effective, sequencing(costs)-free approach that works efficiently across ultra-low to ultra-high cell numbers, while preserving cellular morphology and enabling multimodal profiling. #SpatialOmics #UltraLow #UltraHigh STAMP uses an imaging-based approach to perform high-throughput RNA and protein profiling by stamping cells onto slides compatible with CosMx and Xenium platforms, allowing multimodal profiling in a single run. #Proteomics STAMP supports single-modal (RNA/protein) and multimodal (RNA protein) profiling, enhancing experimental flexibility and scalability. This versatility is essential for large-scale atlases and mixed-sample experiments. #SingleCellAtlas #MultiSampleProfiling STAMP scales easily: from less than 100 to millions of cells. It overcomes limitations in droplet-based systems, where throughput is often constrained by sequencing costs. #HighThroughput STAMP handles diverse sample types: PBMCs, dissociated tumors, nuclei, and stem cells. It also excels with fragile or archived tissues, where traditional methods often fail to yield high-quality data. #ArchivedSamples STAMP eliminates sequencing costs, making large-scale single-cell analysis accessible to more labs. #CostEfficiency Here’s a cost comparison between GEM-X and STAMP-X for RNA profiling: GEM-X RNA (20k cells): $0.0764/cell 1M cells = $76,400 (cost/cell = $0.0764) 2M cells = $152.800 (cost/cell = $0.0764) 3M cells = $229,200 (cost/cell = $0.0764) STAMP-X RNA (1M cells): $0.0075/cell 1M cells = $7,500 (cost/cell = $0.0075) 2M cells = $7,500 (cost/cell = $0.00375) 3M cells = $7,500 (cost/cell = $0.0025) In STAMP cells remain intact after imaging, enabling further downstream applications like histological validation or additional molecular assays, adding value to each sample. #NonDestructiveAnalysis We tested STAMP’s sensitivity by identifying, ultra-rare, circulating tumor cells (CTCs) spiked into PBMCs at 1:100,000. Such sensitivity is essential for clinical diagnostics, particularly in rare cell detection. #CTCs #CancerDiagnostics In a high-throughput immuno-phenotyping experiment, STAMP profiled 1.7M PBMCs, capturing a median of 83 transcripts and 49 genes per cell. This resulted in high-resolution immune profiling. #Immunology #HighThroughputProfiling 31 immune cell states were mapped in PBMCs, capturing rare subpopulations (Th1/Th2/Th17 and NK subtypes). Detailed immune phenotyping is critical for understanding immune diversity in health and disease. #ImmuneMapping Whole cells vs. nuclei: STAMP's ability to profile both whole cells and nuclei is crucial for samples with low RNA content (e.g., archived tissues), increasing the platform’s applicability. #NucleiProfiling #SingleCellOmics STAMP integrates RNA and protein profiling. In cancer cell line profiling, RNA and protein data showed strong correlations, confirming the platform’s robustness in multimodal data collection. #MultimodalProfiling STAMP’s multimodal profiling produced high-resolution immune maps, combining RNA and protein data. This approach is essential for dissecting complex immune states and understanding functional responses. STAMP excels in low-input samples. We demonstrated its ability to accurately profile as few as 100 cells, which is critical for studying rare populations in small samples. #LowInput #RareCell In a BMP4-driven stem cell differentiation model, STAMP captured dynamic changes from pluripotency to mesoderm and endoderm progenitors over multiple timepoints, tracking lineage differentiation. #StemCellDifferentiation #LineageTracing Trajectory analysis shows that STAMP’s resolution makes it a powerful tool for developmental biology and perturbation studies. #DevelopmentalBiology #hESC STAMP allows multi-sample profiling on a single slide, reducing batch effects and improving comparative analysis, particularly in drug response and perturbation studies. #MultiSampleAnalysis #PerturbationScreening STAMP represents a significant advance in single-cell research, offering scalable, multimodal RNA/protein profiling at low cost. Its versatility will support a broad range of research, from basic to clinical. #SingleCellTechnology Lots more coming soon... @DrJasPlummer @hoheyn @pascual_reguant @EmanuelePitino1 @helucro @ximbaozao @irepan_salvador @Kellieiswise @m_mohenska @jc_nietos @cnag_eu @StJudeResearch @ACEpigenetics @M_ayco_N @eliseinsing Bill Flynn, Yutian Liu, Hannah Chasteen

"𝘞𝘢𝘪𝘵 𝘢 𝘮𝘪𝘯𝘶𝘵𝘦. 𝘞𝘢𝘪𝘵 𝘢 𝘮𝘪𝘯𝘶𝘵𝘦 @IdoAmitLab, 𝘢𝘳𝘦 𝘺𝘰𝘶 𝘵𝘦𝘭𝘭𝘪𝘯𝘨 𝘮𝘦 𝘺𝘰𝘶 𝘣𝘶𝘪𝘭𝘵 𝘢 #𝐭𝐢𝐦𝐞𝐦𝐚𝐜𝐡𝐢𝐧𝐞 𝘰𝘶𝘵 𝘰𝘧 𝘢 #𝐬𝐢𝐧𝐠𝐥𝐞𝐜𝐞𝐥𝐥𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲 ?" 🔙to-the-sc-feature(s) kudos @satijalab 💪initiative #singlecellgenomicsday

📣 Exciting advancements! Singleron's #SingleCellTechnology played a pivotal role in a groundbreaking study on tumor progression. Our GEXSCOPE Single Cell RNAseq Library Kit and advanced microfluidic chip were key players. #BreastCancerAwarenessMonth nature.com/articles/s41467-0…

🎧 The wait is over! New episode is out now!🎙️ Join us as we explore the latest in #SingleCell DNA technology from @MissionBio with special guest @FuerteGema. Learn about the Tapestri workflow and more! #singlecelltechnology #MissionBio #podcast #spreaker bit.ly/42zd4Ap

Last Chance to join this course 👇🏻 Exploring the Cutting-Edge World of Single-Cell! thesinglecellworld.com/chall… #singlecell @illumina #singlecelltechnology

Do you know that #singlecell technology can be split in 3 main categories? 🎧 Episode 14 open.spotify.com/episode/3iF… #singlecelltechnology #singlecellmethods @10xGenomics @honeycombbio @Singleron_Bio @Takara_Bio_EU @MGI_Technology @ParseBio @MissionBio @dolomite_micro @QIAGEN

WEBINAR: Dissecting Complex Tissues With Single-cell And Spatial Technologies Date and time: 13th of April at 3pm BST/ 4pm CEST Register at app.livestorm.co/front-line-… #singlecelltechnology #spatialtechnology #tissueanalysis #biologicalcomplexity #cancerresearch #anatech

I wish you all a happy 2023!! With a lot of successful single-cell experiments! 😉 #singlecell #singlecelltranscriptomics #singlecellrnasequencing #singlecelltechnology

Thanks to @BioCongress for giving me the opportunity to present my work today at the Euro-Global Conference on Biotechnology and Bioengineering!! #ECBB2022 #Microarrays #Singlecelltechnology #HIV

Our final group of speakers will take to their soapboxes in 30 mins. Come learn about #SingleCellTechnology from @AdriSuarezGonz, #Protein building blocks from @nr_forde, and #Butterflies from @JaymeLewthwaite!

Great #tweetorial from our postdoc in the Klarman Cell Observatory. @EvgenijFiskin talks about our work on PHAGE-ATAC, a multi-modal #SingleCellTechnology that enables researchers to analyze single cells' proteins, chromatin accessibility, and cellular lineage simultaneously.

@LUMC_Leiden & @tudelft researchers @ahmedElkoussy @liekemichielsen have developed a machine learning method to identify and compile a cellular atlas. Read more about it here: bit.ly/3ftNKEW & in @NatureComms #LUMC #genomics #singlecelltechnology

@LUMC_Leiden & @tudelft researchers @ahmedElkoussy @liekemichielsen have developed a machine learning method to identify and compile a cellular atlas. Read more about it: bit.ly/3ftNKEW & in @NatureComms #LUMC #genomics #singlecelltechnology

We found inspiration for our next cellenONE model in Japan... Single cell technology, stronger than ever!Thanks for the support #quantumdesignjapan #EMBO #singlecelltechnology #artificialintelligence #innovation

#CSTxnDev is now accepting abstracts! Topics include: #epigenetics #evolution #development #singlecelltechnology #transcriptionalregulation & more! bit.ly/2IVyF1J

Broad Fellow Jason Buenrostro is approaching the #genome like an engineer. He is constantly thinking about the unmet needs in disease biology and how his lab can solve them. broadinstitute.org/blog/appr… #BroadFellow #epigenomics #singlecelltechnology

#StefanoPiccolo: A 16 anni dalla pubblicazione del genoma umano abbiamo capito che il vero bersaglio nella cura nel #cancro non è il Dna ma il suo maggior interprete: la cellula. #ricerca #796unipd #singlecell #singlecelltechnology