Identification of cell types underlying thousands of rare diseases and subtraits

Kitty B. Murphy, Bobby Gordon-Smith, Jai Chapman, Momoko Otani, Brian M. Schilder, Nathan G. Skene

Introduction

Rare diseases (RDs) are uncommon as individual diagnoses, but as a group contribute to an enormous disease burden globally. However, partly due the low prevalence and high diversity of individual RDs, this category of diseases is understudied and under-resourced. The advent of large, standardised genetics databases has enabled high-throughput, comprehensive approaches that uncover new insights into the multi-scale aetiology of thousands of diseases. Here, using the Human Phenotype Ontology (9,677 annotated phenotypes) and multiple single-cell transcriptomic atlases (77 human cell types and 38 mouse cell types), we conducted >688,000 enrichment tests (x100,000 bootstrap iterations each) to identify >13,888 genetically supported cell type-phenotype associations.

This repository contains the data and code needed to replicate the analyses in our preprint [insert link to preprint], as well as links to the R packages required (see below).

• KGExplorer: Imports and analyses large-scale biomedical knowledge graphs and ontologies.

• HPOExplorer: Contains extensive functions for easily importing, annotating, filtering, and visualising the Human Phenotype Ontology (HPO) at the disease, phenotype, and gene levels.

• MSTExplorer: Systematically identifies, prioritises, and visualises cell-type-specific gene therapy targets across the phenome.