Professor Damian Smedley
Professor in Computational Genomics
Centre: Clinical Pharmacology
Damian holds a B.Sc. in Biochemistry from Bristol University and PhD in Biochemistry from Cambridge University. Following postdoctoral research as a Kay Kendall Research Fellow at the Institute of Cancer Research and Imperial College, involving identification and characterisation of chromosomal translocations in haematological cancers, he pursued a new, purely computational research career via a M.Sc. in Bioinformatics from Birbeck College. At the European Bioinformatics Institute (EBI) he contributed to the BioMart software system evolving from the advanced query interface of Ensembl to a federated, data management system used by multiple resources worldwide. He then founded and led the mouse informatics team at the EBI before a 3 year spell at the Sanger Institute as a senior manager leading a team of computational biologists linking human disease to the emerging data from the Mouse Genetics Programme and the International Mouse Phenotyping Consortium (IMPC). In 2016 Damian joined the William Harvey Research Institute (WHRI) where his research team continues to work on the IMPC as well as development of the popular Exomiser package for phenotype-aware analysis of rare disease genomes. He is also seconded to Genomics England where he served as Director of Genomic Interpretation for Genomics England, helping to deliver the clinical analysis of rare disease and cancer samples in the 100,000 Genomes Project.
Julius Jacobsen, Tomasz Konopka, Pilar Cacheiro, Valentina Cipriani
Professor Smedley’s research focusses on utilising clinical and model organism phenotype data to better understand human disease.
As a principal investigator for the International Mouse Phenotyping Consortium (IMPC), his team analyses the genotype to phenotype associations emerging from this comprehensive effort to produce the first catalogue of mammalian gene function by knocking out and systematically phenotyping every protein-coding gene in the mouse. Utilising phenotype comparison methods developed with his co-PIs in the Monarch Initiative, his team is able to automatically identify new animal models of known disease genes as well as suggest new candidates for diseases where the causative variants have not yet been identified in human.
This work is extended upon in the Exomiser software package, also developed in conjunction with his collaborators in the Monarch Initiative. Exomiser automates the filtering and prioritisation of coding and non-coding variants called from whole exome or genome sequencing of rare disease families using novel methodologies to prioritise the genes based on the similarity of the patient’s phenotypes to reference knowledge of genotype to phenotype associations from human disease and animal models. This software is widely used by academic researchers, diagnostic laboratories, commercial offering and in large-scale disease sequencing projects such as the US Undiagnosed Disease Network and the UK 100,000 Genomes Project.
For a full list of publications click here
- Robinson PN, Ravanmehr V, Jacobsen JOB, …, Smedley D. Interpretable Clinical Genomics with a Likelihood Ratio Paradigm. American Journal of Human Genetics. 2020 Sep 3;107(3):403-417.
- Cacheiro P, Muñoz-Fuentes V, Murray SA …, Smedley D. Human and mouse essentiality screens as a resource for disease gene discovery. Nature Communications. 2020 11(1):655..
- Cipriani V, Pontikos N, Arno G …, Smedley D An improved phenotype-driven tool for rare Mendelian variant prioritization: benchmarking Exomiser on real patient whole-exome data. 2020 Genes 11(4):460.
- Konopka T, Smedley D. Incremental data integration for tracking genotype-disease associations. PLoS Computational Biology 2020;16(1)
- Cacheiro P, Haendel MA, Smedley D; International Mouse Phenotyping Consortium and the Monarch Initiative. New models for human disease from the International Mouse Phenotyping Consortium. Mammalian Genome. 2019 Jun;30(5-6):143-150.
- Meehan TF, Conte N, West DB, Jacobsen JO … Smedley D. Disease model discovery from 3,328 gene knockouts by The International Mouse Phenotyping Consortium. Nature Genetics 2017Aug;49(8):1231-1238.
- Smedley D, Schubach M, Jacobsen JOB et al. A Whole-Genome Analysis Framework for Effective Identification of Pathogenic Regulatory Variants in Mendelian Disease. American Journal of Human Genetics 2016 Sep 1;99(3):595-606.
- Smedley D, Jacobsen JO, Jäger M, Köhler S, Holtgrewe M, Schubach M, Siragusa E, Zemojtel T, Buske OJ, Washington NL, Bone WP, Haendel MA, Robinson PN .Next-generation diagnostics and disease-gene discovery with the Exomiser. Nature Protocols. 2015 Dec;10(12):2004-15.
- Bone WP, Washington NL, Buske OJ, …, Smedley D. Computational evaluation of exome sequence data using human and model organism phenotypes improves diagnostic efficiency. Genetics in Medicine 2016 Jun;18(6):608-17.
- Smedley D, Robinson PN. Phenotype-driven strategies for exome prioritization of human Mendelian disease genes. Genome Medicine 2015 Jul 30;7(1):81.
- Smedley D, Haider S, Durinck S et al. The BioMart community portal: an innovative alternative to large, centralized data repositories. Nucleic Acids Reseach 2015 Jul 1;43(W1):W589-98.
- Smedley D, Köhler S, Czeschik JC et al. Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases. 2014 Nov 15;30(22):3215-22.
- Robinson PN, Köhler S, Oellrich A … Smedley D. Improved exome prioritization of disease genes through cross-species phenotype comparison. Genome Research. 2014 Feb;24(2):340-8.
External: Prof Peter Robinson (Jackson Laboratory, USA), Dr. Chris Mungall (Lawrence Berkeley National Laboratory, USA), Prof. Melissa Haendel (Oregon State University, USA), Dr. Nigel Collier (University of Cambridge), Dr. Ann-Marie Mallon (MRC-Harwell), Drs. Helen Parkinson and Terrence Meehan (EBI)