spatialGE

# spatialGE

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An R package for the visualization and analysis of spatially-resolved transcriptomics data,
such as those generated with 10X Visium. The **spatialGE** package features a data object 
(STlist: Spatial Transctiptomics List) to store data and results from multiple tissue sections, 
as well as associated analytical methods for:

- Visualization: `STplot`, `gene_interpolation`, `STplot_interpolation` to explore gene 
expression in spatial context.
- Spatial autocorrelation: `SThet`, `compare_SThet` to assess the level of spatial uniformity in 
gene expression by calculating Moran's I and/or Geary's C and qualitatively explore correlations with
sample-level metadata (i.e., tissue type, therapy, disease status).
- Tissue domain/niche detection: `STclust` to perform spatially-informed hierarchical clustering for
prediction of tissue domains in samples.
- Gene set spatial enrichment: `STenrich` to detect gene sets with indications of spatial 
patterns (i.e., non-spatially uniform gene set expression).
- Gene expression spatial gradients: `STgradient` to detect genes with evidence of variation in 
expression with respect to a tissue domain.
- Spatially-informed differential expression: `STdiff` to test for differentially expressed
genes using mixed models with spatial covariance structures to account of spatial dependency
among spots/cells. It also supports non-spatial tests (Wilcoxon's and T-test).

The methods in the initial spatialGE release, technical details, and their utility are presented in
this publication: https://doi.org/10.1093/bioinformatics/btac145. For details on the recently
developed methods `STenrich`, `STgradient`, and `STdiff` please refer to the spatialGE documentation.

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## Installation

The `spatialGE` repository is available at GitHub and can be installed via `devtools`.
```
options(timeout=9999999) # To avoid R closing connection with GitHub
devtools::install_github("fridleylab/spatialGE")
```

## How to use spatialGE

For tutorials on how to use `spatialGE`, please go to:
https://fridleylab.github.io/spatialGE/

The code for `spatialGE` can be found here:
https://github.com/FridleyLab/spatialGE

## [spatialGE-Web](https://spatialge.moffitt.org)

A point-and-click web application that allows using spatialGE without coding/scripting is 
available at https://spatialge.moffitt.org . The web app currently supports Visium outputs and
csv/tsv gene expression files paired with csv/tsv coordinate files.

## How to cite

When using spatialGE, please cite the following publication:

Ospina, O. E., Wilson C. M., Soupir, A. C., Berglund, A. Smalley, I., Tsai, K. Y., Fridley, B. L. 2022. 
spatialGE: quantification and visualization of the tumor microenvironment heterogeneity using spatial 
transcriptomics. Bioinformatics, 38:2645-2647. https://doi.org/10.1093/bioinformatics/btac145


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