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Analysis Strategies for Enriching Single-Cell Phenotyping Data
In this webinar, Kai Tan, of the Children’s Hospital of Philadelphia and Perelman School of Medicine at the University of Pennsylvania discusses GLUER (Integrative Analysis of Multiomics at Single-Cell Resolution), a flexible tool for integration of single-cell multi-omics data and imaging data.
Spatially resolved Transcriptomics via Epitope Anchoring (STvEA) enriches mIHC images with single-cell RNA-seq data, building upon recent experimental procedures for augmenting single-cell transcriptomes with concurrent antigen measurements such as CITE-seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing). Pablo G. Camara of the Perelman School of Medicine at the University of Pennsylvania demonstrates the utility of STvEA by uncovering the architecture of poorly characterized cell types in the murine spleen using published PhenoCycler™ (formerly CODEX®) and CyTOF datasets, and a CITE-seq atlas of the murine spleen that his team has generated.
Integrating complementary data sets provides a powerful tool to study complex biological processes. In this webinar, Dr. Will Wang from Stanford University discusses the use of PhenoCycler spatial proteomic data in parallel with CITE-seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing) data to study tissue regeneration and aging.
This webinar, which caps off our Spatial Multiomics Webinar Series, gathers speakers from prior events in the series to discuss the challenges and benefits of integrating imaging-based single-cell spatial phenotyping data with complementary transcriptomic and genomic datasets.
Our expert panelists review their own strategies for addressing the challenges of integrative multiomic analysis and share best practices for this rapidly evolving field.
The discussion is moderated by Dr. Oliver Braubach of Akoya Biosciences and concludes with a Q&A session in which panelists answer questions from live attendees.
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