VCCC Alliance Precision Oncology Forum

Using functional assay data for variant interpretation

19 September 2025

Using functional assay data for variant interpretation

Alan Rubin and Dr Rehan Villani present an overview of functional assays and an introduction to the MaveDB public repository for MAVE datasets. They share their progress in developing recommendations and training materials for laboratory scientists, as well as case studies demonstrating application of functional data, and finally the new MaveDB clinical interface, designed to support a community of practice interpreting patient variants at scale.

Resolving variants of uncertain significance (VUS) remains an important challenge in clinical genetics for both germline and somatic classification. Functional assays are a potent source of evidence for resolving VUS, and their utility is growing in part due to the widespread adoption of high-throughput techniques such as Multiplexed Assays of Variant Effect (MAVEs).

Chairs

Dr Huiling Xu
Senior Research Fellow, Peter MacCallum Cancer Centre

Dr Joep Vissers
Curation Scientist Team Leader, the University of Melbourne

Speakers

Alan F Rubin PhD
Senior Research Scientist, Walter Eliza Hall Institute (WEHI)

Alan Rubin is a senior research scientist in the WEHI Bioinformatics Division and Co-head of the WEHI Multiplexed Assay Technology Hub. Prior to joining WEHI, Alan completed his PhD in Genome Sciences at the University of Washington. He is a founding member of the executive committee of the Atlas of Variant Effects Alliance, an international collaborative effort to produce multiplexed functional data to inform human disease, as well as the ClinGen/AVE Functional Data Working Group.

Dr Rehan M Villani PhD  MScDG  BScHons
Applied Genomics Researcher, QIMR Berghofer Medical Research Institute

Working to merge functional molecular genetics and clinical genomics implementation, and building on an extensive background of experimental genetics, Dr Villani has more recently focused on building process to translate experimental genetics knowledge into improved genomic diagnostics process. This includes improving the evidence base behind the use of computational prediction and experimental data in non-coding variant classification and in community consultation and capacity building projects for improved knowledge translation into clinical diagnostics practice.

Content warning: The VCCC Alliance Precision Oncology Forum is aimed primarily at a clinical audience and features open discussion about real cases and patients. While these cases are de-identified, the imagery, content and discussion can be graphic.