A Meta-Review of Spatial Transcriptomics Analysis Software

I tiakina i:
Ngā taipitopito rārangi puna kōrero
I whakaputaina i:Cells vol. 14, no. 14 (2025), p. 1060-1079
Kaituhi matua: Gillespie, Jessica
Ētahi atu kaituhi: Pietrzak Maciej, Min-Ae, Song, Chung, Dongjun
I whakaputaina:
MDPI AG
Ngā marau:
Urunga tuihono:Citation/Abstract
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Whakarāpopotonga: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
Puna:Biological Science Database