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characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomics data with nonuniform cellular densities

View the Project on GitHub JEFworks-Lab/MERINGUE

MERINGUE

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MERINGUE characterizes spatial gene expression heterogeneity in spatially resolved single-cell transcriptomics data with non-uniform cellular densities.

The overall approach is detailed in the following publication: Miller, B., Bambah-Mukku, D., Dulac, C., Zhuang, X. and Fan, J. Characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomics data with nonuniform cellular densities. Genome Research. May 2021.

Overview

MERINGUE is a computational framework based on spatial auto-correlation and cross-correlation analysis.

You can use MERINGUE to:

In a manner that:

Installation

To install MERINGUE, we recommend using remotes:

# install.packages(remotes)
require(remotes)
remotes::install_github('JEFworks-Lab/MERingue', build_vignettes = TRUE)

Tutorials

  1. mOB Spatial Transcriptomics Analysis

  2. Multi-section 3D Breast Cancer Spatial Transcriptomics Analysis

  3. 3D Drosophila Spatial Transcriptomics Analysis

  4. Understanding MERINGUE’s Spatial Cross-Correlation Statistic using Simulations

  5. Spatially-informed transcriptional clustering with MERINGUE

Contributing

We welcome any bug reports, enhancement requests, general questions, and other contributions. To submit a bug report or enhancement request, please use the MERINGUE GitHub issues tracker. For more substantial contributions, please fork this repo, push your changes to your fork, and submit a pull request with a good commit message.