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Celloscope: a probabilistic model for marker-gene-driven cell type deconvolution in spatial transcriptomics data.

ABSTRACT: Spatial transcriptomics maps gene expression across tissues, posing the challenge of determining the spatial arrangement of different cell types. However, spatial transcriptomics spots contain multiple cells. Therefore, the observed signal comes from mixtures of cells of different types. Here, we propose an innovative probabilistic model, Celloscope, that utilizes established prior knowledge on marker genes for cell type deconvolution from spatial transcriptomics data. Celloscope outperforms other methods on simulated data, successfully indicates known brain structures and spatially distinguishes between inhibitory and excitatory neuron types based in mouse brain tissue, and dissects large heterogeneity of immune infiltrate composition in prostate gland tissue.

SUBMITTER: Geras A

PROVIDER: S-EPMC10190053 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

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Celloscope: a probabilistic model for marker-gene-driven cell type deconvolution in spatial transcriptomics data.

Geras Agnieszka A Darvish Shafighi Shadi S Domżał Kacper K Filipiuk Igor I Rączkowska Alicja A Szymczak Paulina P Toosi Hosein H Kaczmarek Leszek L Koperski Łukasz Ł Lagergren Jens J Nowis Dominika D Szczurek Ewa E

Genome biology 20230517 1

Spatial transcriptomics maps gene expression across tissues, posing the challenge of determining the spatial arrangement of different cell types. However, spatial transcriptomics spots contain multiple cells. Therefore, the observed signal comes from mixtures of cells of different types. Here, we propose an innovative probabilistic model, Celloscope, that utilizes established prior knowledge on marker genes for cell type deconvolution from spatial transcriptomics data. Celloscope outperforms oth ...[more]

PMID: 37198601

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