/mapgen

R package to perform gene mapping using functionally-informed genetic fine mapping

Primary LanguageROtherNOASSERTION

Mapgen

mapgen is an R package that performs gene mapping based on functionally-informed genetic fine-mapping.

Installation

You can install the development version of mapgen from GitHub with:

# install.packages("remotes")
remotes::install_github("kevinlkx/mapgen")
  • Please install susieR package, if you want to run finemapping with GWAS summary statistics using SuSiE.
  • Please install TORUS software package, if you want to run enrichment analysis using TORUS.

After installing, check that it loads properly:

library(mapgen)

Overview of the workflow

Example workflow from our heart single-cell study:

We developed an integrated procedure that combines single-cell genomics with novel computational approaches to study genetics of complex traits.

Main steps:

  1. Obtain cell-type-resolved open chromatin regions (OCRs) using scATAC-seq and snRNA-seq.
  2. Assess the enrichment of genetic signals of a trait of interest in OCRs across all the cell types.
  3. Perform Bayesian statistical fine mapping on trait-associated loci, using a informative prior that favors likely functional variants located in OCRs of enriched cell types.
  4. Assign the likely cell type(s) through which the causal variants act in most loci using fine-mapped SNPs and its associated cell type information.
  5. Use our novel gene mapping procedure to infer causal genes at each locus.
Overview of the workflow

Overview of the workflow

Please follow the tutorials to learn how to use the package.

Reference

Single-cell genomics improves the discovery of risk variants and genes of cardiac traits. Alan Selewa*, Kaixuan Luo*, Michael Wasney, Linsin Smith, Chenwei Tang, Heather Eckart, Ivan Moskowitz, Anindita Basu, Xin He, Sebastian Pott. medRxiv 2022.02.02.22270312; doi: https://doi.org/10.1101/2022.02.02.22270312