Luke Pilling

@lcpilling.bsky.social

1204 Followers 801 Following

PhD. Genetic epidemiologist Researching mechanisms of chronic long-term conditions, ageing, and drugs @ University of Exeter, UK ❤Rstats. UCU rep✊. Views my own He/him. 🏳️‍🌈ally. 🇬🇧🇪🇺 📷 ShowYourStripes.info W: https://github.com/lcpilling

yodr is a small R package with tools for epidemiology and hypothesis testing

Heatmap of the difference between full and partial genetic correlations for all 2485 disease pairs after adjustment for the genetics of BMI. Pairwise partial genetic correlation analysis between 71 conditions (i.e., 2485 disease pairs). Condition pairs where there was no significant (FDR correction) genetic correlation before or after adjustment, or the adjustment for BMI genetics was non-significant (FDR corrected), are coloured white. Data shown is the proportion change in genetic correlation between condition pairs after adjustment for BMI genetics (where the change is statistically significant after FDR correction). https://www.nature.com/articles/s43856-025-01347-y/figures/2

My 526 GitHub contributions (mostly commits) over the last 12 months. Never on Saturdays, rarely on Sundays, except where I have personal nerd projects apparently

Cartoon by the excellent Allison Horst (https://allisonhorst.com/git-github). Includes a quote from Hadley Wickham and Jenny Bryan that says “Using a Git commit is like using anchors and other protection when climbing…if you make a mistake you can’t fall past the previous commit. Commits are also helpful to others, because they show your journey, not just the destination.” On the right, two little monsters climb a cliff face. Their ropes are secured by several anchors, each labeled “Commit”. Three monsters on the ground support the climbers.

View of the River Exe running through the Quay in sunny Exeter.

Cumulative incidence of haemochromatosis-associated clinical outcomes in males HFE C282Y homozygotes in UK Biobank, stratified into two groups based on transferrin saturation polygenic score (highest vs. lowest quintile). This shows clearly that even within the high-risk C282Y group, likelihood of adverse consequences is influenced by non-HFE genetic variants that also impact iron

Professor Jane Masoli introducing how secondary care electronic healthcare records data (Epic) can be used for research

My new fidget spinner. I am holding it in the auditorium

Google maps showing the route from Exeter to Swindon via Bristol

Mary Mancini speaking on her experience as a patient with comorbodities

Dr Olivia Murrin presenting her slides

Professor Tim Frayling presenting the GEMINI slides

Professor Jane Masoli on stage

Screenshot of my R console running the few commands to get character/string output of extreme p-values

Map showing the route from Exeter up to the centre in Filton where they ran tests and then processed it into a form that can be given to a patient in need. Once it was ready it was sent to the University Hospital, Birmingham where it will help to save or improve someone's life.

Screenshot of the ukbrapR package GitHub website, showing "dark mode" toggled, and the Articles drop-down menu

Screenshot of the paper abstract. We used Transferrin Saturation as the clinical marker of iron

R syntax to use ukbrapR::get_rap_phenos