https://github.com/neurogenomics/magma_celltyping
Find causal cell-types underlying complex trait genetics
https://github.com/neurogenomics/magma_celltyping
genomics gwas magma single-cell single-cell-omics snps statistical-genetics
Last synced: 2 months ago
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Find causal cell-types underlying complex trait genetics
- Host: GitHub
- URL: https://github.com/neurogenomics/magma_celltyping
- Owner: neurogenomics
- Created: 2018-05-04T09:38:10.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2025-02-25T16:21:20.000Z (4 months ago)
- Last Synced: 2025-03-30T19:05:06.346Z (3 months ago)
- Topics: genomics, gwas, magma, single-cell, single-cell-omics, snps, statistical-genetics
- Language: R
- Homepage: https://neurogenomics.github.io/MAGMA_Celltyping
- Size: 248 MB
- Stars: 82
- Watchers: 5
- Forks: 32
- Open Issues: 11
-
Metadata Files:
- Readme: README.Rmd
Awesome Lists containing this project
README
---
title: ""
author: "`r rworkflows::use_badges()`"
date: "
README updated: `r format( Sys.Date(), '%b-%d-%Y')`
"
output:
github_document
---
```{r, echo=FALSE, include=FALSE}
pkg <- read.dcf("DESCRIPTION", fields = "Package")[1]
repo <- gsub("https://github.com/","",
read.dcf('DESCRIPTION', fields = 'URL'))
description <- read.dcf("DESCRIPTION", fields = "Description")[1]
```
## Introduction
This R package contains code used for testing which cell types can explain the heritability signal from GWAS summary statistics. The method was described in our [2018 Nature Genetics paper](https://www.nature.com/articles/s41588-018-0129-5).
This package takes GWAS summary statistics + single-cell transcriptome specificity data (in [EWCE](https://github.com/NathanSkene/EWCE)'s CellTypeData format) as input. It then calculates and returns the enrichment between the GWAS trait and the cell-types.
## Installation
### R
Install `MAGMA.Celltyping` as follows:
```R
if(!require("remotes")) install.packages("remotes")
remotes::install_github("`r repo`")
library(`r pkg`)
```
### MAGMA
`MAGMA.Celltyping` now installs the command line software MAGMA automatically
when you first use a function that relies on [MAGMA](https://ctg.cncr.nl/software/magma) (e.g. `celltype_associations_pipeline`).
If you prefer, you can later install other versions of MAGMA with:
```R
MAGMA.Celltyping::install_magma(desired_version="",
update = TRUE)
```
## Documentation
### [Website](https://neurogenomics.github.io/MAGMA_Celltyping/)
### [Getting started](https://neurogenomics.github.io/MAGMA_Celltyping/articles/MAGMA.Celltyping.html)
### [Docker/Singularity](https://neurogenomics.github.io/MAGMA_Celltyping/articles/docker)
## Using older versions
With the release of `MAGMA_Celltyping` 2.0 in January 2022, there have been a number of [major updates and bug fixes](https://github.com/neurogenomics/MAGMA_Celltyping/pull/93).
- Only R>4.0.0 is supported. To use this package with older versions of R, install with:`remotes::install_github("neurogenomics/MAGMA_Celltyping@01a9e53")`
## Bugs/fixes
Having trouble? Search the [Issues](https://github.com/neurogenomics/MAGMA_Celltyping/issues)
or submit a new one.
Want to contribute new features/fixes? [Pull Requests](https://github.com/neurogenomics/MAGMA_Celltyping/pulls) are welcomed!
Both are most welcome, we want the package to be easy to use for everyone!
## Citations
If you use the software then please cite:
> [Skene, et al. Genetic identification of brain cell types underlying schizophrenia. Nature Genetics, 2018.](https://www.nature.com/articles/s41588-018-0129-5)
The package utilises the [MAGMA](https://ctg.cncr.nl/software/magma) software developed in the Complex Trait Genetics Lab at VU university (not us!) so please also cite:
> [de Leeuw, et al. MAGMA: Generalized gene-set analysis of GWAS data. PLoS Comput Biol, 2015.](https://journals.plos.org/ploscompbiol/article?id=10.1371%2Fjournal.pcbi.1004219)
If you use the EWCE package as well then please cite:
> [Skene, et al. Identification of Vulnerable Cell Types in Major Brain Disorders Using Single Cell Transcriptomes and Expression Weighted Cell Type Enrichment. Front. Neurosci, 2016.](https://www.frontiersin.org/articles/10.3389/fnins.2016.00016/full)
If you use `MungeSumstats` to format your summary statistics then please cite:
> [Murphy, Schilder, & Skene, MungeSumstats: a Bioconductor package for the standardization and quality control of many GWAS summary statistics, Bioinformatics, Volume 37, Issue 23, 1 December 2021, Pages 4593–4596, https://doi.org/10.1093/bioinformatics/btab665](https://doi.org/10.1093/bioinformatics/btab665)
If you use the cortex/hippocampus single cell data associated with this package then please cite the following papers:
> [Zeisel, et al. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science, 2015.](https://doi.org/10.1126/science.aaa1934)
If you use the midbrain and hypothalamus single cell datasets associated with the 2018 paper then please cite the following papers:
> [La Manno, et al. Molecular Diversity of Midbrain Development in Mouse, Human, and Stem Cells. Cell, 2016.](https://doi.org/10.1016/j.cell.2016.09.027)
> [Romanov, et al. Molecular interrogation of hypothalamic organization reveals distinct dopamine neuronal subtypes. Nature Neuroscience, 2016.](https://doi.org/10.1038/nn.4462)
## Contact
### [Neurogenomics Lab](https://www.neurogenomics.co.uk/)
UK Dementia Research Institute
Department of Brain Sciences
Faculty of Medicine
Imperial College London
[GitHub](https://github.com/neurogenomics)
[DockerHub](https://hub.docker.com/orgs/neurogenomicslab)