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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
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# Giotto Suite
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[](https://www.gnu.org/licenses/gpl-3.0)
[](https://github.com/RubD/Giotto/actions/workflows/R-CMD-check.yaml)
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**Website change!**
We have created a new [readthedocs website](https://giottosuite.readthedocs.io/en/latest/#) to further improve and simplify Giotto documentation and to make it easier to use Giotto. It aggregates information from both the original Giotto package and our extended Giotto Suite, which is our extended work-in-development version.
- www.spatialgiotto.com links to the original [master version](https://giottosuite.readthedocs.io/en/master/). The old master pkgdown documentation can still be found at https://rubd.github.io/Giotto_site/
- www.giottosuite.com links to the extended [suite version](https://giottosuite.readthedocs.io/en/latest/). The old suite pkgdown documentation can still be found at https://drieslab.github.io/Giotto_site_suite/
Giotto Suite is a major upgrade to the Giotto package that provides tools to process, analyze and visualize **spatial multi-omics data at all scales and multiple resolutions**. The underlying framework is generalizable to virtually all current and emerging spatial technologies. Our Giotto Suite prototype pipeline is generally applicable on various different datasets, such as those created by state-of-the-art spatial technologies, including *in situ* hybridization (seqFISH+, merFISH, osmFISH, CosMx), sequencing (Slide-seq, Visium, STARmap, Seq-Scope, Stereo-Seq) and imaging-based multiplexing/proteomics (CyCIF, MIBI, CODEX). These technologies differ in terms of resolution (subcellular, single cell or multiple cells), spatial dimension (2D vs 3D), molecular modality (protein, RNA, DNA, ...), and throughput (number of cells and analytes).
The package is in heavy development. Please check back often!
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## References
- [Dries, R., Zhu, Q. et al. Giotto: a toolbox for integrative analysis and visualization of spatial expression data. Genome Biology (2021).](https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02286-2) \doi{10.1186/s13059-021-02286-2}
- [Dries, R., Chen, J. et al. Advances in spatial transcriptomic data analysis. Genome Research (2021).](https://genome.cshlp.org/content/31/10/1706.long) \doi{10.1101/gr.275224.121}
- [Del Rossi, N., Chen, J. et al. Analyzing Spatial Transcriptomics Data Using Giotto. Current Protocols (2022).](https://currentprotocols.onlinelibrary.wiley.com/doi/abs/10.1002/cpz1.405) \doi{10.1002/cpz1.405}