The Human Phenotype Ontology (HPO) is a controlled vocabulary of phenotypic abnormalities encountered in human disease. It currently contains over 18,000 hierarchically organised terms. Each term in the HPO describes a phenotypic abnormality, ranging from very broad phenotypes (e.g. “Abnormality of the nervous system”) down to extremely specific phenotypes (e.g. “Decreased CSF 5-hydroxyindolacetic acid concentration”).
The HPO is currently being used in thousands of exome and genome sequencing projects around the world to aid in the interpretation of human variation, in clinical practice to support differential diagnosis and to annotate patient information, and in research to understand the role of rare variants in human health and disease. The HPO was developed by the Monarch Initiative in collaboration with The Jackson Laboratory.
HPOExplorer is an R package with extensive functions for easily
importing, annotating, filtering, and visualising the Human Phenotype
Ontology (HPO) at the disease, phenotype, and
gene levels. By pulling fresh data directly from official resources like
HPO,
Monarch and
GenCC, it ensures tightly controlled version
coordination with the most up-to-date data available at any given time
(with the option to use caching to boost speed). Furthermore, it can
efficiently reorganise gene annotations into sparse matrices for usage
within downstream statistical and machine learning analysis.
HPOExplorer was developed by the Neurogenomics
Lab at Imperial College London, along
with valuable feedback provided by the HPO team. This package is still
actively evolving and growing. Community engagement is welcome and any
suggestions can be submitted as an
Issue or Pull
Request.
Within R:
if(!require("BiocManager")) install.packages("BiocManager")
BiocManager::install("neurogenomics/HPOExplorer")
library(HPOExplorer)A quick tutorial on how to get started with HPOExplorer.
HPOExplorer is also available via
DockerHub.
Click
here
for instructions on how to create a Docker or Singularity container with
HPOExplorer and Rstudio pre-installed.
If you use HPOExplorer, please cite:
Kitty B. Murphy, Robert Gordon-Smith, Jai Chapman, Momoko Otani, Brian M. Schilder, Nathan G. Skene (2023) Identification of cell type-specific gene targets underlying thousands of rare diseases and subtraits. medRxiv, https://doi.org/10.1101/2023.02.13.23285820
utils::sessionInfo()## R version 4.3.1 (2023-06-16)
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