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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Identification of host–pathogen-disease relationships using a scalable multiplex serology platform in UK Biobank
Journal article
Mentzer AJ. et al, (2022), Nature Communications, 13
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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
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Recommendations for improving statistical inference in population genomics.
Journal article
Johri P. et al, (2022), PLoS biology, 20
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A unified genealogy of modern and ancient genomes.
Journal article
Wohns AW. et al, (2022), Science (New York, N.Y.), 375
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Topic modelling with ICD10-informed priors identifies novel genetic loci associated with multimorbidities in UK Biobank
Preprint
Zhang Y. et al, (2022)