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Cell-type deconvolution methods for spatial transcriptomics
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DOI：10.1038/s41576-025-00845-y.png)
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Abstract
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Spatial transcriptomics is a powerful method for studying the spatial organization of cells, which is a critical feature in the development, function and evolution of multicellular life. However, sequencing-based spatial transcriptomics has not yet achieved cellular-level resolution, so advanced deconvolution methods are needed to infer cell-type contributions at each location in the data. Recent progress has led to diverse tools for cell-type deconvolution that are helping to describe tissue architectures in health and disease. In this Review, we describe the varied types of cell-type deconvolution methods for spatial transcriptomics, contrast their capabilities and summarize them in a web-based, interactive table to enable more efficient method selection. Cell-type deconvolution methods are often needed to analyse spatial transcriptomic data to recover cell-type distributions. In this Review, the authors describe the process of cell-type deconvolution, contrast the tools available and highlight important considerations for which tool to use.
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