Fiona Cunningham

Fiona Cunningham
Team Leader - Cunningham team: Genome Interpretation

PhD in bioinformatics, University of Cambridge, 2014. At EMBL-EBI since 2008, Variation Annotation Team Leader since 2016, Genome Interpretation Team Leader since 2021.

Dr Fiona Cunningham is interested in problems where building large-scale systems for genomic data can lead to fundamental biological insights, particularly for understanding genomic variation. At EMBL-EBI she is responsible for genome interpretation and variation resources. Her team developed Ensembl's Variant Effect predictor (VEP), the software tool for annotating variation data.
Fiona is part of the senior management for Ensembl (, a genome information system, and led the creation of the variation and phenotype data in Ensembl. Fiona shares leadership of Ensembl’s genome interpretation strategy and has overall responsibility for the variation resources in Ensembl. In collaboration with the NHGRI, she is one of the PIs for the GWAS Catalog and formally, she led the Variant Annotation task team for the Global Alliance for Genomic Health project (GA4GH). 
Fiona is committed to open data and standards, in particular to share data and facilitate the transfer of research knowledge into valuable resources. In collaboration with the NCBI in the USA, Fiona leads the Matched Annotation from NCBI and EMBL-EBI (MANE) initiative, which aims to release a genome-wide transcript set with only one well-supported transcript per protein-coding locus. All transcripts in the MANE set will perfectly align to GRCh38 and will represent 100% identity between RefSeq and Ensembl/GENCODE. She also worked on the development of reference sequences, called LRG (Locus Reference Genomic) sequences, a stable data standard for reporting clinical variants with support for legacy sequences as part of the Transforming Genomic Medicine Initiative (TGMI). 

Prior to EMBL-EBI, Dr Cunningham worked at the Wellcome Trust Sanger Institute, Cold Spring Harbor Laboratory, and at deCODE Genetics in Iceland.

ORCID iD: 0000-0002-7445-2419

Tel:+ 44 (0) 1223 494 612 / Fax:

Cunningham team

The Human Genome Project generated a reference sequence that was a significant milestone in genomics, but only one in a series of steps toward the goal of personalised medical treatment. To realise the potential of genomics in this context, what is needed is an understanding of transcription, and interpretation of genomic variation, phenotype and disease data in different populations and across different species. Open access to catalogues of existing knowledge of genomic and variation annotation, and to tools for interpretation are fundamental for progress in biology, from basic research to translational genomics in the clinic.

The Genome Interpretation team focus on providing fundamental reference resources that underpin genomic research. We provide robust and reliable reference resources for consistent genome and variant annotation in any species. Through the GENCODE consortium we aim to provide complete annotation for human and detailed annotation for mouse. To support variation annotation, we catalogue and store large-scale data, and develop methods and tools to facilitate integration and broad access to these data. Without a catalogue and annotation of these data, understanding the genome sequence of an individual and assessing disease risk is impossible.

We create novel workflows and databases to integrate data for Ensembl, resulting in one of the largest catalogues of annotated transcript, variant, phenotype, trait and disease data for vertebrate species. To aid the interpretation of genetic variants in their evolutionary and disease context, we develop the Ensembl Variant Effect Predictor (VEP), a software tool for in silico annotation of variants using the data in Ensembl, and other data access methods including visual displays. We collaborate with NCBI's RefSeq group on the Matched Annotation from the NCBI and EMBL-EBI (MANE) initiative, which aims to standardise transcript use across browsers and resources. For this we will generate a genome-wide transcript set in human that identifies pairs of Ensembl/GENCODE and RefSeq transcripts that are 100% identical and match the GRCh38 assembly. This is the evolution of our collaboration to annotate genes associated with disease and create stable sequences, Locus Reference Genomic (LRG), for clinical reporting of variants. In collaboration with the Deciphering Developmental Disorders project, we have developed Gene2Phenotype, a framework for manually curated gene-to-phenotype or disease associations, stored in a structured manner for high throughput access. This can be used with the VEP to filter results from genome and exome sequencing studies. The team also provides data coordination for the International Genome Samples Resource (IGSR). 



Team members

  • Ola Austine-Orimoloye
  • If Barnes
  • Ruth Bennett
  • Andrew Berry
  • Alexandra Bignell
  • Claire Davidson
  • Sarah Donaldson
  • Reham Fatima
  • Adam Frankish
  • Jose Manuel Gonzalez Martinez
  • Matthew Hardy
  • Zoe Hollis
  • Toby Hunt
  • Sarah Hunt
  • Mike Kay
  • Diana Lemos
  • Jane Loveland
  • Ernesto Lowy
  • Joannella Morales
  • Jonathan Mudge
  • Andrew Parton
  • Helen Schuilenburg
  • Ranjit Shanker Sukumaran
  • Marie-Marthe Suner
  • Anja Thormann
  • Elizabeth Wass