GeoMx Digital Spatial Profiler (DSP) vs. CZ CELLxGENE Discover

Effectively tackle the challenges posed by tissue heterogeneity and the complex nature of microenvironments through the use of the GeoMx Digital Spatial Profiler (DSP), which is distinguished as the most adaptable and robust spatial multi-omic platform designed for the analysis of both FFPE and fresh frozen tissue samples. Unlike other spatial biology tools, GeoMx provides a non-destructive method for profiling RNA and protein expression across diverse tissue compartments and cell populations, all facilitated by an automated and scalable workflow that integrates seamlessly with traditional histology staining techniques. You have the capability to spatially profile the complete transcriptome alongside more than 570 protein targets, either individually or in combination, utilizing sample inputs like whole tissue sections, tissue microarrays (TMAs), or organoids. Opting for GeoMx DSP places you at the leading edge of spatial biology, enhancing your efforts in biomarker discovery and hypothesis validation. This platform empowers you to accurately delineate relevant boundaries, allowing for biology-driven profiling that zeroes in on the tissue microenvironments and cell types that are most critical to your research endeavors. By employing this groundbreaking method, your analyses not only become more comprehensive but also finely tuned to the specific biological questions you aim to address. Ultimately, this paves the way for deeper insights and more impactful findings in your field of study.

Select two customized cell groups by leveraging metadata to identify their most distinctly expressed genes. Use the vast repository of millions of cells from the integrated CZ CELLxGENE database for comprehensive analysis. Engage in dynamic examinations of datasets to explore how gene expression patterns are shaped by spatial, environmental, and genetic factors through an intuitive no-code interface. This approach allows researchers to gain insights into existing datasets or utilize them as a springboard to uncover novel cell subtypes and states. Census enables access to any tailored segment of standardized cell data within the CZ CELLxGENE, with options for exploration in both R and Python environments. Immerse yourself in an interactive encyclopedia that features over 700 cell types, complete with detailed definitions, marker genes, lineage details, and related datasets all accessible in a single platform. In addition, researchers can browse and acquire an extensive array of standardized data collections, alongside more than 1,000 datasets that illuminate the functions of both healthy mouse and human tissues, significantly enhancing the study of cellular biology. This resource serves as an invaluable tool for scientists striving to deepen their understanding of cellular dynamics and gene expression, ultimately driving innovation in the field. Furthermore, the user-friendly interface promotes collaborative efforts among researchers, fostering a community of shared knowledge and discoveries.