Spatial multi-omics technologies are transforming our understanding of complex biological systems with unprecedented detail. STOmics' Stereo-seq offers nanoscale resolution and an expansive field of view of up to 160 cm². In this issue, we highlight recent advances, key resources, and notable publications that showcase the power of Stereo-seq across neuroscience, disease research, and beyond.

In this blog, we explore the principles of spatial gene co-expression, evaluate the performance of computational algorithms on Stereo-seq datasets, and highlight case studies demonstrating its translational potential.

This blog summarizes key concepts from that session, examining different annotation algorithms and their performance. Our goal is to equip you with foundational knowledge and guide your choice of algorithm for annotating your own datasets.

We present benchmark results comparing eight cell segmentation tools across four typical staining conditions (DAPI, ssDNA, H&E, and mIF). Our data-driven recommendations provide researchers with guidance for selecting optimal segmentation algorithms based on specific experimental conditions.

Building on our previous blog "Stereo-seq Image Processing: Essential Steps and Their Key Points ", which detailed core image processing steps, this blog now explore practical solutions to common analysis challenges using StereoMap's tools and third-party software integration.

This blog distills the webinar (Stereo-seq image analysis)’s key concepts and explains the fundamentals behind these processing stages. Our goal is to provide you with the essential knowledge for Stereo-seq image analysis and to assist in troubleshooting any related issues you may encounter.

In this blog, we will introduce the key output files generated by SAW, explain their generation process, and outline the methods for utilizing or converting them for advanced analysis.

An international team of scientists from leading research institutes worldwide collaborated to conduct pioneering research in building a 3D spatiotemporal modeling framework—Spateo (https://github.com/aristoteleo/spateo-release). Their accomplishment was published as a featured article in Cell, titled “Spatiotemporal modeling of molecular holograms”.

CellBin, an image processing pipeline embedded in SAW (Stereo-seq Analysis Workflow), the primary bioinformatics software for Stereo-seq data analysis, plays a crucial role. The pipeline includes several image processing algorithms tailored for various Stereo-seq applications, such as a unique nuclei segmentation algorithm that adapts to different sample staining methods.

Stereo-seq is a sequencing-based spatial multi-omics platform that is not limited by pre-designed probes or panels and can capture the whole transcriptome for scientific discovery.