Philip Haycock
Research Fellow In Genetic Epidemiology at MRC Integrative Epidemiology Unit
Bristol, England, United Kingdom
Summary
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Senior🎓
Top SchoolPhilip Haycock is a genetic epidemiologist and research fellow at the MRC Integrative Epidemiology Unit, University of Bristol, with over a decade of experience applying Mendelian randomization to uncover modifiable causes of chronic diseases. He co-founded MR-Base and contributes to its flagship TwoSampleMR R package, enhancing instrument extraction, data clumping, result formatting, and multi-exposure visualization—work that supports large international consortia and the wider genomics community. His research portfolio spans cancer, coronary heart disease, and type II diabetes and leverages major resources such as UK Biobank, CARDIoGRAM, DIAGRAM and ALSPAC to generate causal and mechanistic insights. Trained with a PhD in genetic epidemiology from Cambridge and earlier degrees with distinction in human genetics, he blends deep statistical genetics expertise with practical tool development that accelerates reproducible causal inference.
10 years of coding experience
2 years of employment as a software developer
MSc, Human Genetics, Disctinction, MSc, Human Genetics, Disctinction at University of the WitwatersrandDoctor of Philosophy (PhD), Genetic epidemiology, Doctor of Philosophy (PhD), Genetic epidemiology at University of Cambridge
English, Portuguese, Afrikaans
Github Skills (7)
data-visualizations10
data-visualization10
data-visualisation10
ggplot10
r-package10
r10
bioinformatics9
Programming languages (2)
Github contributions (5)
MRCIEU/TwoSampleMR
May 2016 - Nov 2022
R package for performing 2-sample MR using MR-Base database
Role in this project:
Data Scientist
Data ScientistContributions:3 reviews, 71 commits, 1 PR in 6 years 7 months
Contributions summary:Philip primarily contributed to the development and refinement of functions within an R package designed for two-sample Mendelian Randomization (MR) analysis. Their work involved modifying existing functions, like `extract_instruments` and `clump_data`, to improve the process of retrieving and preparing genetic instrument data. They also added a new function, `format_mr_results`, for formatting MR results and created, and updated multiple iterations of the `forest_plot_1-to-many` function, and associated helper functions, enhancing the visualization capabilities for multiple exposures and outcomes, and expanding the flexibility of existing plotting functions.
r-packagedatabaserstats
mightyphil2000/fatty-acids
Nov 2019 - Apr 2022
Contributions:16 commits, 13 pushes in 2 years 5 months
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