The Giotto package consists of two modules, Giotto Analyzer and Viewer (see www.spatialgiotto.com), which provide tools to process, analyze and visualize single-cell spatial expression data. The underlying framework is generalizable to virtually all currently available spatial datasets. We recently demonstrated the general applicability on 10 different datasets created by 9 different state-of-the-art spatial technologies, including in situ hybridization (seqFISH+, merFISH, osmFISH), sequencing (Slide-seq, Visium, STARmap) and imaging-based multiplexing/proteomics (CyCIF, MIBI, CODEX). These technologies differ in terms of resolution (single cell vs multiple cells), spatial dimension (2D vs 3D), molecular modality (protein vs RNA), and throughput (number of cells and genes). More information and documentation about the latest (developmental) version of Giotto Analyzer can be found at https://rubd.github.io/Giotto/.

• R (>= 3.5.1)
• Python (>= 3.0)
• Windows, MacOS, Linux

See FAQs for additional information.

You can install (~1-5 mins) Giotto with:

library(remotes)  # if not installed: install.packages('remotes')
# to install the latest version
remotes::install_github("RubD/Giotto")

This is necessary to run all available analyses, including Leiden / Louvain clustering and to build and use the interactive visualization tool. An alternative, but less flexible, R version for Louvain clustering is also available. It is advisable to install everything within a specific conda environment and specify the python path at the beginning with createGiottoInstructions() or in the R function itself when required.

Required python modules: pandas / igraph / networkx / leidenalg

pip installation one-liner:

pip3 install pandas python-igraph networkx python-louvain leidenalg

If pip install does not work, try installing within a conda environment:

conda install -c anaconda pandas
conda install -c conda-forge python-igraph
conda install -c anaconda networkx
conda install -c conda-forge python-louvain
conda install -c conda-forge leidenalg

See HMRF installation instructions.

pip3 install --user jsbeautifier
pip3 install --user giotto-viewer --no-cache #add --no-deps if do not wish to upgrade dependency
pip3 install --user smfish-image-processing --no-cache #add --no-deps if do not wish to upgrade dependency

• see https://github.com/RubD/spatial-datasets to find raw and pre-processed input data and Giotto scripts (in progress).
• typical run time range for the different datasets on a personal computer is around 10~45 mins.
• click on the image and try them out yourself.

• Dries, R. et al. Giotto, a pipeline for integrative analysis and visualization of single-cell spatial transcriptomic data. bioRxiv 701680 (2019). doi:10.1101/701680

• Eng, C.-H. L. et al. Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+. Nature 1 (2019). doi:10.1038/s41586-019-1049-y

• Zhu, Q., Shah, S., Dries, R., Cai, L. & Yuan, G.-C. Identification of spatially associated subpopulations by combining scRNAseq and sequential fluorescence in situ hybridization data. Nature Biotechnology (2018). doi:10.1038/nbt.4260