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Updated: Jan 12, 2026

Mining Spatial Transcriptomics Datasets using DeepSpaceDB
Published on: September 5, 2025
Connectogenomics: edges-first spatial biology
Reem Yasser1, Mingrui Yu2, Nianchao Qian3
1Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, USA.
Abstract:
Spatial omics maps cell types and spatial context together. Current methods fall into two streams: mapping coordinates (where things are) and measuring connections between cells that are in contact or close proximity. We introduce the term connectogenomics as a practical umbrella for sequencing assays that directly record such contacts as a network. Combining coordinates with measured contacts lets us verify whether apparent neighbors truly interact and turn network features - such as contact density or hub centrality - into quantitative readouts. We propose a framework with four complementary tiers and a feedback loop: directly measured molecular contacts can validate coordinate-based analyses, while coordinate maps guide where to prioritize contact measurements. We illustrate this approach in cancer immunotherapy, development, and pooled genetic screens.
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