Gil McVean
FMedSci, FRS
Professor of Statistical Genetics
My research covers several areas in the analysis of genetic variation, combining the development of methods for analyzing high throughput sequencing data, theoretical work and empirical analysis. Of particular interest are: the analysis of recombination from population genetic data, dissecting signals of disease association within the HLA, methods for inferring genealogical history from DNA sequence data and de novo sequence assembly for the discovery of genetic variation. I am a member of the Department of Statistics and the Oxford Big Data Institute.
Recent publications
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Optimal strategies for learning multi-ancestry polygenic scores vary across traits
Journal article
Lehmann B. et al, (2023), Nature Communications, 14
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The Type 2 Diabetes Knowledge Portal: An open access genetic resource dedicated to type 2 diabetes and related traits.
Journal article
Costanzo MC. et al, (2023), Cell Metab
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Age-dependent topic modelling of comorbidities in UK Biobank identifies disease subtypes with differential genetic risk
Preprint
Jiang X. et al, (2022)
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Age-dependent topic modelling of comorbidities in UK Biobank identifies disease subtypes with differential genetic risk
Preprint
Jiang X. et al, (2022)
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Mouse fetal growth restriction through parental and fetal immune gene variation and intercellular communications cascade.
Journal article
Kaur G. et al, (2022), Nature communications, 13