What is Giotto?

Giotto is a comprehensive and open-source toolbox for spatial data analysis and visualization. The analysis module provides end-to-end analysis by implementing a wide range of algorithms for characterizing tissue composition, spatial expression patterns, and cellular interactions. Furthermore, single-cell RNAseq data can be integrated for spatial cell-type enrichment analysis. The visualization module allows users to interactively visualize analysis outputs and imaging features. Giotto is applicable to a wide range of spatial technologies and platforms.

Description

• Giotto provides a flexible framework for common single-cell processing steps such as:

  • Quality control

  • Normalization

  • Dimension reduction

  • Clustering and cell type annotation

• To facilitate the analysis of recently emerging high-throughput, but lower-resolution spatial transcriptomic technologies, such as 10X Genomics Visium and Slide-seq, Giotto has 3 implemented algorithms for estimating the spatial enrichment of different cell types by integration of known gene signatures or single-cell RNAseq expression and annotation data.

• Spatial information is retained through the formation of a spatial grid and/or a spatial proximity network, which is used to:

  • Identify spatial genes

  • Extract continuous spatial-expression patterns

  • Identify discrete spatial domains using HMRF

  • Explore cell-type/cell-type spatial interaction enrichment or depletion

  • Calculate spatially increased ligand-receptor expression in cells of interacting cell type pairs

  • Find interaction changed genes (ICG): genes that change expression in one cell type due to interaction with a neighboring cell type

• Giotto provides a number of options to visualize both 2D and 3D data and the outcome of Giotto can be interactively explored using Giotto Viewer which allows you to overlay the obtained results with raw or additional images of the profiled tissue section(s).

Cite Giotto

Dries, R., Zhu, Q., Dong, R., Eng, C. H. L., Li, H., Liu, K., … & Yuan, G. C. (2021). Giotto: a toolbox for integrative analysis and visualization of spatial expression data. Genome biology, 22(1), 1-31. <https://pubmed.ncbi.nlm.nih.gov/33685491/>

License

Authors and Developers

Ruben Dries	Author, Maintainer
Qian Zhu	Author
Huipeng Li	Author
Rui Dong	Author
Guo-Cheng Yuan	Author

References

1. Han X, Wang R, Zhou Y, Fei L, Sun H, Lai S, et al. Mapping the mouse cell atlas by microwell-Seq. Cell. 2018;173:1307. doi: 10.1016/j.cell.2018.05.012.

2. Tabula Muris Consortium, overall coordination, logistical coordination, organ collection and processing, library preparation and sequencing, Computational data analysis, et al. Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris. Nature. 2018;562:367–72.

3. Lubeck E, Coskun AF, Zhiyentayev T, Ahmad M, Cai L. Single-cell in situ RNA profiling by sequential hybridization. Nat. Methods. 2014. p. 360–361.

4. Chen KH, Boettiger AN, Moffitt JR, Wang S, Zhuang X. RNA imaging. Spatially resolved, highly multiplexed RNA profiling in single cells. Science. 2015;348:aaa6090. doi: 10.1126/science.aaa6090.

5. Ståhl PL, Salmén F, Vickovic S, Lundmark A, Navarro JF, Magnusson J, et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science. 2016;353:78–82. doi: 10.1126/science.aaf2403.

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