In neurogenomics/MultiEWCE: Multi-Scale Target Explorer

pkg <- read.dcf("DESCRIPTION", fields = "Package")[1]
title <- read.dcf("DESCRIPTION", fields = "Title")[1]
description <- gsub("\n"," ",read.dcf("DESCRIPTION", fields = "Description")[1])
URL <- read.dcf('DESCRIPTION', fields = 'URL')[1]
owner <- strsplit(URL,"/")[[1]][4]
repo <-strsplit(URL,"/")[[1]][5]

Introduction

Many genes have been associated with diseases Multi-Scale Target Explorer (MSTExplorer) systematically identifies, prioritises, and visualises cell-type-specific gene therapy targets across the phenome.

Core functionalities include:

1. Conducting phenotype x cell type genetic association tests at scale

• The Human Phenotype Ontology (integrated with gene annotations from OMIM / DECIPHER / ORPHANET) is used as the source of phenotype gene signatures. Each gene-phenotype associated is given a continuous score that approximates the current strength of evidence for the association (using data derived from GenCC).

• Whole-body scRNA-seq atlases from humans (across multiple developmental stages) are used as a data-driven source of cell type-specific gene markers.

• The underlying association tests are designed for both speed and accuracy using memory-efficient data structures, and a highly parallelisable implementation of Generalised Linear Regression (GLM). For example, associations for all pairwise combinations of >11k phenotypes x >200 cell types (>2,200,000 associations) can be in <30 minutes on a Macbook laptop with 10 CPU cores).

2. Inferring multi-scale causal graphs of disease

MSTExplorer allows users to easily infer and construct multi-scale causal graphs of Diseases (blue nodes) -> Phenotypes (purple nodes) -> Cell types (orange nodes) -> Genes (yellow nodes).

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See here for more example networks..

3. Prioritising cell-type-specific gene therapy targets

MSTExplorer also provides a comprehensive and customisable pipeline that can be run via a single function (prioritise_targets()) to produce the most promising cell-type-specific gene therapy targets across the phenome.

Installation

Within R:

if(!require("BiocManager")) install.packages("BiocManager")

BiocManager::install("`r paste(owner,repo,sep='/')`")
library(`r pkg`)

Documentation

Website

Get started

Docker/Singularity Container

Citation

If you use r pkg, please cite:

r utils::citation(pkg)$textVersion

Contact

Neurogenomics Lab

UK Dementia Research Institute
Department of Brain Sciences
Faculty of Medicine
Imperial College London
GitHub

Session Info

utils::sessionInfo()

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neurogenomics/MultiEWCE documentation built on April 17, 2025, 9:27 p.m.