scMultiMap

scMultiMap is an R package for inferring cell-type-specific peak-gene associations using single-cell multimodal data. It implements the statistical method proposed in the manuscript Cell-type-specific mapping of enhancer and target genes from single-cell multimodal data, accepted in principle by Nature Communications. (The link to the published article will be posted once available.)

Installation

You can install scMultiMap from GitHub using devtools:

# Load devtools for installing R packages from GitHub
library(devtools)

# Install scMultiMap from GitHub
install_github("ChangSuBiostats/scMultiMap")

Vignettes

The following vignettes provide detailed use cases for scMultiMap:

1. Introduction to scMultiMap: Learn how to infer peak-gene associations in cell types using 10x Multiome data on PBMC.

2. scMultiMap for disease-control studies: Identify differentially associated peak-gene pairs in disease-control studies.

3. scMultiMap for integrative analysis with GWAS results: Integrate scMultiMap results with genome-wide association studies (GWAS) to explore the regulatory roles of GWAS variants in disease-associated cell types.

scMultiMap_analysis for reproducibility

To reproduce the analysis in Cell-type-specific mapping of enhancer and target genes from single-cell multimodal data, please visit our dedicated GitHub repository containing the source code used in the paper: scMultiMap_analysis.

Contact us

For issues or feature requests, please visit GitHub Issues.

Reference and Updates

Chang Su, Dongsoo Lee, Peng Jin and Jingfei Zhang. (2024). Cell-type-specific mapping of enhancer and target genes from single-cell multimodal data. Accepted in principle by Nature Communications.