Navigating the spatial biology landscape can feel like standing in front of a massive soundboard, trying to balance dozens of sliders at once. Every platform promises single-cell or near single-cell resolution,
but each hits that benchmark through fundamentally different engineering.
Multiomics research has fundamentally changed what it means to outsource NGS. It is no longer sufficient to find a vendor that can only sequence a library. Modern programs integrating RNA-seq, single-cell profiling, spatial transcriptomics, epigenomics, and long-read sequencing demand a partner with platform depth, rigorous quality standards, and the operational efficiency to keep budgets and timelines intact. Choosing the wrong partner does not just slow you down—it can compromise the integrity of your entire project.
The spatial transcriptomics field provides unrivaled insights into gene expression within intact tissue architecture which is crucial for both exploratory discovery and targeted hypothesis testing. Two paradigms stand out: the 10x Genomics Visium HD platform and Xenium Prime (e.g., Xenium Prime 5K imaging-based assay). This post dissects their core technologies, strengths, and optimal use cases for advanced genomic research.
Signios Biosciences details how advanced single-cell and spatial transcriptomics support neuroscience research into Alzheimer’s, FTD, TBI, and Friedreich’s Ataxia, aiding new therapy development.
Signios Biosciences details how advanced single-cell and spatial transcriptomics support neuroscience research into Alzheimer’s, FTD, TBI, and Friedreich’s Ataxia, aiding new therapy development.
Traumatic brain injury (TBI) poses complex challenges for researchers aiming to understand cellular responses post-injury. Professor Michelle H. Theus of Virginia Tech partnered with MedGenome to shed light on the cellular dynamics underlying injury progression and recovery on a murine TBI model using single-cell and spatial transcriptomics.
Spatial analysis has become an indispensable tool in unraveling the complexities of biological systems. From understanding gene function to dissecting tissue microenvironments, spatial data holds the key to unlocking valuable insights into biological processes. However, harnessing the full potential of spatial data requires not only sophisticated analytical techniques but also considerable computational resources and expertise.
