Giotto Suite

Default branch change!
With the release of v3.3.0 the default branch of Giotto has been moved from @master to @suite. If you want to install the original master version use devtools::install_github("drieslab/Giotto@master"). Visit the Giotto Discussions page for more information.

Github Repository changes!
The Giotto github repository has moved to https://github.com/drieslab/Giotto and the associated spatial datasets have been moved to https://github.com/drieslab/spatial-datasets.

Website change!
We have created a new readthedocs website 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. 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. 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!
For a version history/changelog, please see the NEWS file.

References

• Dries, R., Zhu, Q. et al. Giotto: a toolbox for integrative analysis and visualization of spatial expression data. Genome Biology (2021).
• Dries, R., Chen, J. et al. Advances in spatial transcriptomic data analysis. Genome Research (2021).
• Del Rossi, N., Chen, J. et al. Analyzing Spatial Transcriptomics Data Using Giotto. Current Protocols (2022).