The OAK Guide

This guide provides an explanation of basic concepts in OAK, how to use both the Python library, and the command line.

For a quick introduction, see the Tutorial

Contents:

• OAK Basics
  • What is an ontology and why would I want to access one?
  • Ontology languages, standards, and formats
  • Core OAK concepts
• Identifying entities: CURIEs and URIs
  • Prefix maps
  • Querying prefixmaps
  • Non-default prefixmaps
  • Structure of identifiers
  • Further reading
• Primary Labels
  • Looking up labels
  • Custom label annotation properties
  • Multilingual ontologies
  • Other edge cases
  • Further reading
• Aliases and Synonyms
  • Use Cases
    • Search
    • Text mining and NLP
    • Different aliases for different communities
    • Different Languages
  • Different approaches to representing synonym metadata
  • Representation of synonyms in OAK
    • Simple Core Model
    • Obo Graph Data Model
• Mappings and Cross-References
  • SSSOM
  • Mappings in OAK
    • In Python
  • Directionality of mappings
  • Support for SSSOM
  • Generating Mappings
  • Further reading
• Obsoletion
  • Looking up obsoleted entities
  • Conventions and standards
    • obsolete entities should not be in the signature of any logical axiom
    • obsolete entities should be accompanied by metadata that provides additional context for humans and machines
  • Merged entities
  • Further Reading
• Relationships and Graphs
  • Exploring relationships
  • Graph Traversal and Relation Graph Reasoning
    • Graph Traversal Strategies
    • Examples of where entailment yields more
    • Examples of where graph traversal yields more ancestors than entailment
    • Which strategy should I use?
    • A note on entailed direct edges
  • Further notes on OWL and Graph Projection
• Associations and Curated Annotations
  • Background
  • Association support in OAK
    • Data Model
    • Selecting association sources
  • Further reading
• Enrichment and Over-Representation Analysis
  • Background
  • Concepts
    • Statistical Significance in Enrichment
    • Redundancy Filtering
  • Performing Enrichment Analysis
    • Using the Command Line
    • Visualizing Results
    • Programmatic Interface
  • Interpreting Results
  • Advanced Options
    • Pseudo-enrichment
    • Custom Background Sets
    • Cross-Ontology Enrichment
  • Companion Notebooks
  • Further Reading
• Computing Similarity between Entities
  • Background
  • Concepts
    • Jaccard Similarity
    • Jaccard Similarity of ontology terms
    • Information Content
    • Ensemble Scoring of term pairs
    • Other similarity measures
    • Aggregate measures for comparing entities
    • Vector-based approaches
  • Implementations
    • Default Implementation
    • Ubergraph
    • Semsimian
  • Companion Notebooks
  • Further reading
• Learning More