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SMART: spatial transcriptomics deconvolution using marker-gene-assisted topic model
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DOI：10.1186/s13059-024-03441-1.png)
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Abstract
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While spatial transcriptomics offer valuable insights into gene expression patterns within the spatial context of tissue, many technologies do not have a single-cell resolution. Here, we present SMART, a marker gene-assisted deconvolution method that simultaneously infers the cell type-specific gene expression profile and the cellular composition at each spot. Using multiple datasets, we show that SMART outperforms the existing methods in realistic settings. It also provides a two-stage approach to enhance its performance on cell subtypes. The covariate model of SMART enables the identification of cell type-specific differentially expressed genes across conditions, elucidating biological changes at a single-cell-type resolution.
Keywords:
Spatial transcriptomics
Deconvolution
Semi-supervised
Topic models
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