Spatial Omics Team

Revealing hidden cellular landscapes

Spatial transcriptomics is an innovative technique that combines spatial information with gene expression data, allowing researchers to visualize and analyze the location and activity of thousands of genes within a tissue sample.

This Spatial Omics Team strives to develop new and open-source techniques where we can provide an understanding of cellular function and interaction in their native spatial context.

Highlighted spatial omics papers

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Mnich

MultiNicheNet: a flexible framework for differential cell-cell communication analysis from multi-sample multi-condition single-cell transcriptomics data

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Robin Browaeys, Jeroen Gilis, Chananchida Sang-Aram, Pieter De Bleser, Levi Hoste, Simon Tavernier, Diether Lambrechts, Yvan Saeys & Ruth Seurinck

bioRxiv 2023

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Spotless_small

Spotless, a reproducible pipeline for benchmarking cell type deconvolution in spatial transcriptomics

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Chananchida Sang-aram, Robin Browaeys, Ruth Seurinck & Yvan Saeys

eLife 2024