bioRxiv · 10.1101/2025.11.20.688607
Orchestrating Spatial Transcriptomics Analysis with Bioconductor
Abstract
Spatial transcriptomics technologies provide spatially-resolved measurements of gene expression through assays that can either target selected genes or capture transcriptome-wide expression profiles. The complexity and variability of these technologies and their associated data necessitate multi-step workflows integrating diverse computational methods and software packages. We provide a freely accessible, open-source, continuously updated and tested online book containing reproducible code examples, datasets, and discussion about data analysis workflows for spatial omics data using Bioconductor in R, including interoperability with Python.
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Crowell, H. L., Dong, Y., Billato, I., Cai, P., Emons, M., Gunz, S., Guo, B., Li, M., Mahmoud, A., Manukyan, A., Pages, H., Panwar, P., Rao, S., Sargeant, C. J., Shepherd Kern, L., Ramos, M., Sun, J., Totty, M., Carey, V. J., Chen, Y., Collado-Torres, L., Ghazanfar, S., Hansen, K. D., Martinowich, K., Maynard, K. R., Patrick, E., Righelli, D., Risso, D., Tiberi, S., Waldron, L., Gottardo, R., Robinson, M. D., Hicks, S. C., Weber, L. M.. 2025-11-21. Orchestrating Spatial Transcriptomics Analysis with Bioconductor. https://doi.org/10.1101/2025.11.20.688607
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