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Spatial Multiomics Webinar Series

Analysis Strategies for Enriching Single-Cell Phenotyping Data

In this multi-part webinar series, our expert speakers review analytical frameworks and algorithms to integrate imaging-based single-cell spatial phenotyping data with complementary transcriptomic and genomic datasets. High-plex cell phenotyping methods like single-cell RNA-seq capture the deep cellular heterogeneity of samples, but cell behavior is a function of all that surrounds it. Imaging-based spatial phenotyping platforms enable researchers to visualize and analyze cell diversity, interactive networks, and cellular behavior across whole tissue sections. Both types of data have complementary features, which give researchers the ability to merge information about a cell’s proteome and transcriptome with its single-cell, spatial context. This webinar series highlights the latest advances driving integrative multiomic analysis.

Integrative Analysis of Single-Cell Omics and Imaging 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.

  • Learn about a general computational framework (GLUER) for integrating single-cell omics and imaging data
  • Hear strategies to evaluate performance of data integration methods
  • See the utility of integration methods for understanding cell-cell communication

Video

Speaker

Kai Tan, PhD

Children’s Hospital of Philadelphia and Perelman School of Medicine at the University of Pennsylvania

Transcriptome-Guided Analysis of Highly Multiplexed Immunohistochemistry Images

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.

  • Learn about current challenges in the analysis of mIHC images
  • Understand the concept of STvEA and the algorithmic steps involved
  • Get familiarized with the computational analyses enabled by STvEA
  • See several examples of the application of STvEA

Video

Speaker

Pablo G. Camara, PhD

Perelman School of Medicine at the University of Pennsylvania

Enriching Spatial Proteomic Data with Parallel CITE-seq Analysis Elucidates Multiomic Changes with Aging

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.

  • Learn about the use of multiplex imaging to study spatial dynamics of skeletal muscle regeneration and molecular determinants of aging
  • Understand how to design and align CITE-seq experiments to enrich PhenoCycler data
  • See how to use single-cell resolution spatial transcriptomes to assess cell-cell signaling

Video

Speaker

Will Wang, PhD

Stanford University School of Medicine

Panel Discussion: Analysis Strategies for Enriching Single-Cell Spatial Phenotyping Data

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.

Video

Speaker

Oliver Braubach, PhD

Akoya Biosciences