Deciphering spatial ecotypes from spatial, single-cell, and bulk transcriptomic data

Spatial EcoTyper is a versatile framework designed for the systematic identification of spatial cellular communities, termed spatial ecotypes, from single-cell spatial transcriptomics data. In addition, it provides unified methods for the recovery of spatial ecotypes across multiple data modalities, including spatial transcriptomics, single-cell RNA-seq, and bulk transcriptomic datasets.

Overview of Spatial EcoTyper

Spatial EcoTyper is available as an R package, with comprehensive documentation accessible at https://digitalcytometry.github.io/spatialecotyper. Additionally, Spatial EcoTyper can be used via the web platform at https://spatialecotyper.stanford.edu/ (will be available soon), a user-friendly interface for recovering spatial ecotypes from various data sources, including spatial transcriptomics (e.g. MERSCOPE, Visium, etc), single-cell RNA-seq, and bulk gene expression datasets.

We provide 6 comprehensive tutorials illustrating the functionalities included in the SpatialEcoTyper R package. The first tutorial demonstrates how to identify spatial ecotypes from a single-cell spatial transcriptomics data. The second demonstrates how to identified conserved spatial ecotypes across multiple samples. The third demonstrates how to develop NMF models for recovery of spatial ecotypes from unseen data. The remaining tutorials introduce how to recover spatial ecotypes from spatial transcriptomics, scRNA-seq, and bulk RNA-seq datasets.

• Tutorial 1: Discovery of Spatial Ecotypes from A Single Sample
• Tutorial 2: Discovery of Spatial Ecotypes from Multiple Samples
• Tutorial 3: Development of NMF Models for Spatial Ecotype Recovery
• Tutorial 4: Recovery of Spatial Ecotypes from Spatial Transcriptomics Data
• Tutorial 5: Recovery of Spatial Ecotypes from Single-Cell Gene Expression Data
• Tutorial 6: Recovery of Spatial Ecotypes from Bulk Gene Expression Data

Note: Spatial EcoTyper depends extensively on Seurat for key processes like dimensionality reduction, UMAP embedding, clustering, and visualization. Initially developed using Seurat v4.3, the tool has been thoroughly tested and validated with Seurat v5. Although UMAP embeddings and clustering results show slight differences between Seurat v4 and v5, the overall consistency remains strong, ensuring that core biological insights are preserved across both versions.

Installation

Spatial EcoTyper is available as an R package and can be installed via the BiocManager package directly from the R console.

if(!"BiocManager" %in% installed.packages()){
  install.packages("BiocManager")
}

## Install dependencies
BiocManager::install(c("remotes", "Seurat", "NMF", "dplyr", "pals",
                       "data.table", "ComplexHeatmap", "googledrive", 
                       "glmGamPoi", "immunogenomics/presto"))

## Install SpatialEcoTyper
BiocManager::install("digitalcytometry/spatialecotyper")

Troubleshooting dependency installation

• ERROR: dependency ‘GetoptLong’ is not available for package ‘ComplexHeatmap’

  If the installation within R console fails, you can try installing the necessary packages via conda install or mamba install.

  conda install bioconda::bioconductor-complexheatmap

• Failed to install 'presto' from GitHub: HTTP error 401. Bad credentials

  To resolve this issue, you’ll need to authenticate using a personal access token (PAT). You can generate a GitHub personal access token following the GitHub's documentation. After generating the token, set it as an environment variable in R using the following code. Replace "YOUR_TOKEN" with your actual token:

  ## Set the token in your R environment:
  Sys.setenv(GITHUB_PAT="YOUR_TOKEN")
  
  ## Install the package from GitHub:
  BiocManager::install("immunogenomics/presto")

Install SpatialEcoTyper from source code

The source code of **Spatial EcoTyper** is available at https://github.com/digitalcytometry/spatialecotyper. After downloading the package, you can install it from the source code using the command:

install.packages("SpatialEcoTyper.tar.gz", repos = NULL)

Contribution

If you encounter any bugs or have suggestions for improvements, please feel free to open an issue or submit a pull request. Your feedback and contributions help us make the tool better for everyone.

License

Please see the LICENSE file.

Authors

Spatial EcoTyper was developed in the Newman Lab by Wubing Zhang.

Citation

If you use Spatial EcoTyper, please cite: