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A Meta-Review of Spatial Transcriptomics Analysis Software

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Publicado en:Cells vol. 14, no. 14 (2025), p. 1060-1079
Autor principal: Gillespie, Jessica
Otros Autores: Pietrzak Maciej, Min-Ae, Song, Chung, Dongjun
Publicado:
MDPI AG
Materias:
Accuracy
Software packages
Tumor microenvironment
Gene expression
Cell interactions
Histology
Datasets
Transcriptomics
Localization
Communication
Software
Benchmarks
Acceso en línea:Citation/Abstract
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Resumen:Spatial transcriptomics combines gene expression data with spatial coordinates to allow for the discovery of detailed RNA localization, study development, investigating the tumor microenvironment, and creating a tissue atlas. A large range of spatial transcriptomics software is available, with little information on which may be better suited for particular datasets or computing environments. A review was conducted to detail the useful metrics when choosing appropriate software for spatial transcriptomics analysis. Specifically, the results from benchmarking studies that compared software across four key areas of spatial transcriptomics analysis (tissue architecture identification, spatially variable gene discovery, cell–cell communication analysis, and deconvolution) were assimilated into a single review that can serve as guidance when choosing potential spatial transcriptomics analysis software.
ISSN:2073-4409
DOI:10.3390/cells14141060
Fuente:Biological Science Database