Annotation and Annotation Resources

^ with content from Lori Shepherd Kern, Martin Morgan and James W. MacDonald CSAMA 2026

Johannes Rainer

Institute for Biomedicine, Eurac Research

Introduction

Data analysis

  • Annotation: external data fed into an analysis to make sense of quantified entities.

Annotation

  • put a (new or different) label on an entity
  • entity: something measured with an assay (RNA, molecule, cell)
  • label: commonly used (standard) identifier (e.g. gene name)
  • sounds trivial, but is very important task in computational biology
  • examples:
    • map positions on the genome to transcripts
    • map genes to biological pathways
    • annotate cell types based on presence of marker genes
  • 🎯 enable or assist in interpretation; make biological sense of assay data.

In this presentation

  • 1️⃣ provide some general information on annotation
  • 2️⃣ give you an overview on available annotation resources
  • 3️⃣ short use cases (with code)

1️⃣ General information on annotation

What do we need for annotation?

  • 1️⃣ an annotation resource: reference information on entities or a mapping of one type of identifiers to another.
  • 2️⃣ a rule that defines how to assign labels to entities
    • annotation through similarity: sequence similarity, spectral similarity
    • direct mapping

What do we need for annotation?

  • 1️⃣ an annotation resource: reference information on entities or a mapping of one type of identifiers to another.
  • 2️⃣ a rule that defines how to assign labels to entities
  • examples
    • map between gene identifiers (Ensembl, NCBI, …)

What do we need for annotation?

  • 1️⃣ an annotation resource: reference information on entities or a mapping of one type of identifiers to another.
  • 2️⃣ a rule that defines how to assign labels to entities
  • examples
    • annotate through sequence similarity: map short reads to genome