Spatial transcriptomics combines high-plex quantification with the spatial resolution of immunohistochemistry. This technology classifies tissue based on total mRNA or protein within the morphological context of FFPE or frozen tissues. Spatial expression mapping is a powerful tool for examining cellular interactions, tissue and tumor heterogeneity, pathogenicity, and response to therapy.
We offer spatial profiling at multiple levels of resolution utilizing 10X Genomics® Visium HD® and NanoString® GeoMx® Digital Spatial Profiler platforms. These novel technologies perform simultaneous, in situ spatial analysis from a single FFPE or frozen tissue section. You can select from a host of discovery-focused panels with the potential for customization. Together with our epigenetic and single-cell sequencing solutions, you have access to the most cutting-edge technologies available to study gene expression from every angle and every level.
Digital special profiling (DSP) is important for analyzing cellular heterogeneity and intracellular interactions, especially in the context of drug therapy response. Important advantages of DSP:
Digital spatial profiling (DSP) is a technique used to identify and quantify mRNA and protein expression in tissues such as FFPE (formalin-fixed paraffin-embedded) samples, fresh frozen tissue sections, tissue microarrays, and core needle biopsies.
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High-resolution full mapping of the transcriptome across tissue sections while preserving spatial context
High-plex profiling of RNA and protein expressions within multiple regions of interest in tissue samples
In this tech note we explore how the spatial transcriptomics platform, Visium HD®, bridges the gap between histology and gene expression profiling, offering precise biomarker discovery and cellular mapping within complex tissues to support research across oncology, immunology, and developmental biology.
With this two-part webinar series, go beyond traditional transcriptomics and learn about the various NGS approaches available for gene expression analysis. In part 1, we take an in-depth look at various gene expression approaches, including RNA-Seq, single-cell RNA-Seq, digital spatial profiling, and more. In part 2, we explore the data generated from these approaches and how they can complement each other and confirm findings.
For information on our NGS platforms as well as recommended configurations of your projects, please visit the NGS Platforms page. Azenta does not guarantee data output or quality for sequencing-only projects.