A tool for analyzing single-cell SNP data with focus on organ transplant.
Overview
variantCell is an R-based computational tool designed to analyze single-cell SNP data with a particular focus on transplant settings. It works with widely-used single-cell genomics workflows to identify, characterize, and visualize SNPs at cellular resolution, enabling researchers to distinguish donor from recipient cells and quantify SNPs that may influence transplant outcomes.
The package provides a comprehensive framework for processing CellSNP and Vireo output, normalizing SNP counts, and performing differential SNP analysis across cell types or clinical conditions. With built-in visualization capabilities, users can explore variant distributions within genes of interest and create SNP heatmaps across cell clusters.
Unlike existing approaches that analyze variants at the bulk tissue level, variantCell leverages single-cell resolution to reveal cell type-specific genetic signals and heterogeneity within transplanted tissues. This approach offers unique insights into the genetic factors driving transplant rejection, immune response variation, and cellular chimerism in complex tissues, with applications extending to cancer, development, and other areas where genetic mosaicism is biologically significant.
Core Dependencies
R6, data.table, Matrix, ggplot2, cowplot, GenomicRanges, IRanges, AnnotationHub, matrixStats, ensembldb, circlize, ComplexHeatmap
Optional Dependencies
Seurat: If using Seurat objects as input (not required if using data frames), SingleCellExperiment: If using SingleCellExperiment objects as input Parallel processing findDESNPs function: parallel, doParallel, foreach
Getting Started
To add samples to the SNP database, the package requires: - An output directory from CellSNP along with cell metadata (as a Seurat object, dataframe, or SingleCellExperiment) - Cell prefixes can be optionally specified when adding sample data to match cell IDs to integrated data
For transplant mode, you’ll also need: - A Vireo output directory - Specification of which donors are ‘Recipient’ and ‘Donor’ (can be determined using the process_vireo helper function)
After adding samples, a SNP database can be built using the buildSNPDatabase function, enabling:
Finding SNPs present or absent in specific groups
Performing cell (or group)-level differential SNP expression analysis (uses parallel processing)
SNPs can be visualized:
Plotting SNPs for specific genes
Creating heatmaps of SNPs within cell clusters / groups
Installation
Install from GitHub
Check if devtools is installed, install if needed
if (!requireNamespace("devtools", quietly = TRUE)) { install.packages("devtools") }
devtools::install_github("potterae/variantCell")
Citation
If you use this software, please cite:
Andrew Potter, Don Hayes (in preparation). variantCell: A tool for single-cell SNP analysis. GitHub: https://github.com/potterae/variantCell