A Meta-Review of Spatial Transcriptomics Analysis Software
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| Veröffentlicht in: | Cells vol. 14, no. 14 (2025), p. 1060-1079 |
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MDPI AG
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| Online-Zugang: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 2073-4409 | ||
| 024 | 7 | |a 10.3390/cells14141060 |2 doi | |
| 035 | |a 3233106347 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231441 |2 nlm | ||
| 100 | 1 | |a Gillespie, Jessica |u Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA; jessica.gillespie@osumc.edu (J.G.); maciej.pietrzak@osumc.edu (M.P.) | |
| 245 | 1 | |a A Meta-Review of Spatial Transcriptomics Analysis Software | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 653 | |a Accuracy | ||
| 653 | |a Software packages | ||
| 653 | |a Tumor microenvironment | ||
| 653 | |a Gene expression | ||
| 653 | |a Cell interactions | ||
| 653 | |a Histology | ||
| 653 | |a Datasets | ||
| 653 | |a Transcriptomics | ||
| 653 | |a Localization | ||
| 653 | |a Communication | ||
| 653 | |a Software | ||
| 653 | |a Benchmarks | ||
| 700 | 1 | |a Pietrzak Maciej |u Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA; jessica.gillespie@osumc.edu (J.G.); maciej.pietrzak@osumc.edu (M.P.) | |
| 700 | 1 | |a Min-Ae, Song |u Division of Environmental Health Science, College of Public Health, The Ohio State University, Columbus, OH 43210, USA; song.991@osu.edu | |
| 700 | 1 | |a Chung, Dongjun |u Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA; jessica.gillespie@osumc.edu (J.G.); maciej.pietrzak@osumc.edu (M.P.) | |
| 773 | 0 | |t Cells |g vol. 14, no. 14 (2025), p. 1060-1079 | |
| 786 | 0 | |d ProQuest |t Biological Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3233106347/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3233106347/fulltextwithgraphics/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3233106347/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |