Tangram, gimVI and SpaGE outperformed other integration methods for predicting the spatial distributions of RNA transcripts, while Cell2location, SpatialDWLS and RCTD were the top-performing methods for the cell type deconvolution of spots in histological sections.
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References
Biancalani, T. et al. Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram. Nat Methods 18, 1352–1362 (2021).
Lopez, R. et al. A joint model of unpaired data from scRNA-seq and spatial transcriptomics for imputing missing gene expression measurements. Preprint at arXiv https://doi.org/10.48550/arXiv.1905.02269 (2019).
Abdelaal, T. et al. SpaGE: Spatial Gene Enhancement using scRNA-seq. Nucleic Acids Res. 48, e107 (2020).
Kleshchevnikov, V. et al. Cell2location maps fine-grained cell types in spatial transcriptomics. Nat. Biotechnol. https://doi.org/10.1038/s41587-021-01139-4 (2022).
Dong, R. & Yuan, G. C. SpatialDWLS: accurate deconvolution of spatial transcriptomic data. Genome Biol. 22, 145 (2021).
Cable, D. M. et al. Robust decomposition of cell type mixtures in spatial transcriptomics. Nat. Biotechnol. 40, 517–526 (2022).
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This is a summary of: Li, B. et al. Benchmarking spatial and single-cell transcriptomics integration methods for transcript distribution prediction and cell type deconvolution. Nat. Methods https://doi.org/10.1038/s41592-022-01480-9 (2022).
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Benchmarking spatial and single-cell transcriptomics integration methods. Nat Methods 19, 656–657 (2022). https://doi.org/10.1038/s41592-022-01481-8
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DOI: https://doi.org/10.1038/s41592-022-01481-8