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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Publisher Correction: Inferring whole-genome histories in large population datasets
Journal article
Kelleher J. et al, (2019), Nature Genetics, 51, 1660 - 1660
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Inferring whole-genome histories in large population datasets
Journal article
Kelleher J. et al, (2019), Nature Genetics, 51, 1330 - 1338
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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, (2019)
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Detection of simple and complex de novo mutations without, with, or with multiple reference sequences
Journal article
Garimella KV. et al, (2019)
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Mapping the drivers of within-host pathogen evolution using massive data sets.
Journal article
Palmer DS. et al, (2019), Nature communications, 10