A General Framework for Comparing Embedding Visualizations Across Class-Label Hierarchies
At VIS 2024, Ozette’s former intern, Trevor Manz, presented work conducted in collaboration with Nils Gehlenborg’s lab at Harvard Medical School. The presentation outlined our work on a general framework for comparing embedding visualizations across class-label hierarchies. The paper is published in the IEEE TVCG journal. Ozette uses this methodology to identify and visualize meaningful compositional differences between two single-cell datasets.
Pharmacodynamic and response biomarkers in the monotherapy arm of a phase 1 trial of CTX-471, a novel anti-CD137 agonist antibody
At SITC 2024, Ozette’s partner, Compass, presented findings from the monotherapy arm of their CTX-471 phase 1 trial. A novel anti-CD137 agonist antibody, CTX-471 treatment elicited changes consistent with increased anti-tumor immunity, including changes in natural killer cell activation status and tumor-specific expression of markers. These data identify potential biomarkers for selection of patients with a higher probability of responding to CTX-471 therapy. Read more here.
High-dimensional spectral cytometry paired with computational technology provides insights into the cellular features of healthy donor blood products to accelerate allogeneic cell therapy development
At SITC 2024, Ozette’s Head of Immunology, Ashley Wilson, presented how we use our 48-color spectral cytometry assay and AI-driven analysis platform to better identify optimal donors for allogeneic cell therapy. Analyzing immunophenotypes across different blood products from healthy donors, we found that donor characteristics, such as chronic viral infection and mobilization efficacy, can impact the suitability of blood products for allogeneic cell therapy development. Learn more by downloading the event poster here.
Pairing high-parameter spectral flow cytometry with CITE-seq using a novel automated artificial intelligence-based analysis platform to characterize immunophenotypes and cell states
At SITC 2024, Ozette’s Zoey Zhou presented how Ozette applied our AI-driven analysis platform to streamline the analysis of paired spectral flow cytometry and CITE-seq datasets and enhance immune cell profiling. By analyzing PBMC samples from healthy donors, we identified robust immunophenotypes to inform CITE-seq differential expression analysis, revealing distinct gene expression profiles associated with defined protein expression phenotypes. Download the event poster here to learn more.
From Endpoints to Discovery, see how Ozette’s platform assesses assay precision, specimen stability, and the effect of sample storage on immune cells.
This year at CYTO, Ozette showcased “An automated approach to high-parameter spectral flow cytometry assay validation using a novel AI/ML platform to assess the precision and stability of predefined biomarker endpoints in the context of a 48-color pan-immune profiling panel.” If you weren’t able to catch us at the conference or want to take a closer look, download the event poster here.
Applying Ozette Discovery™ to CITE-seq data to identify predictors of disease.
Methods such as CITE-seq simultaneously measure RNA and protein expression at a single cell level, but the protein expression data is frequently underutilized. Download our preprint to learn how we harness Ozette Discovery™ to achieve instantaneous in silico sorting of granular cell phenotypes, enabling identification of COVID-19-associated cell populations and precise RNA-seq profiling in mixed samples.
Effective comparison of single-cell embedding visualizations.
At ISMB 2023, Ozette’s Trevor Manz lead a lively panel on effective comparison of single-cell embedding visualizations. To better understand the approach, challenges, and conclusions, learn more by downloading the event poster here.
Automated gating and antigen-specific T cells subset discovery using FAUST and COMPASS on ICS data.
At ISMB 2022, Ozette Computational Biologist Malisa Smith, and Ozette Co-Founder Evan Greene, PhD VP of Quantitative Methods discussed automated gating and antigen-specific T cells subset discovery using FAUST and COMPASS on ICS data as well as how they reanalyzed a published Intracellular Cytokine Staining (ICS) dataset. Download the poster to learn more about their presentation.
Discovering data transformations for effective visualization of single-cell embeddings.
At ISMB 2022, Ozette’s Fritz Lekschas, PhD, Head of Visualization Research lead a fascinating discussion about data transformations for effective visualization of single-cell embeddings. If you weren’t able to attend, take a look at this beautiful and though provoking work.
From assay to endpoints, see how Ozette’s proprietary processes deliver results.
Recently, at CYTO 2023, we showcased how Ozette Endpoints™ and Ozette Discovery™ technologies leverage Artificial Intelligence and Machine Learning to deliver robust computational analysis pipelines and allow for rapid insights into complex high-dimensional data. View process details, methods, and case study examples in our detailed conference poster.