Jerome Kelleher
BSc, PhD
Robertson Fellow; Group Leader in Biomedical Data Science
My research revolves around developing efficient algorithms to solve fundamental problems in genomics, and implementing these algorithms in production quality, open source software. This programme takes advantage of the unique structure of genetic data, combining theoretical population genetics with classical computer science. I lead development of tskit, a growing library of fundamental operations for population and statistical genomics with a welcoming open source community.
I am an advocate for the importance of software in research and a member of the UK Research Software Engineer Association.
Recent publications
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Analysis-ready VCF at Biobank scale using Zarr
Journal article
KELLEHER J. and JEFFERY B., (2025), GigaScience
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Accessible, realistic genome simulation with selection using stdpopsim.
Journal article
Gower G. et al, (2025), bioRxiv
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Estimating evolutionary and demographic parameters via ARG-derived IBD.
Journal article
Huang Z. et al, (2025), PLoS genetics, 21
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A general and efficient representation of ancestral recombination graphs
Journal article
KELLEHER J. and WONG HY., (2024), Genetics
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Analysis-ready VCF at Biobank scale using Zarr.
Journal article
Czech E. et al, (2024), bioRxiv