Palamara Lab
University of Oxford, Department of Statistics.
We are currently recruiting a postdoctoral research associate (3-year position) in statistical and machine learning methods for genomics. Click here for the full job posting and application details. Deadline: May 2, 2025
We are a research group based at Oxford University’s Department of Statistics and the Centre for Human Genetics, working at the intersection of computer science, statistics, and genetics. Our work focuses on developing statistical and machine learning algorithms to enable novel analyses of large human genomic datasets. Specific areas of research in human genomics include:
- Developing algorithms for the simulation, reconstruction, and analysis of large-scale genealogical data (e.g., gene genealogies, haplotype sharing, phasing, imputation).
- Studying demographic events and evolutionary parameters, including migration, population expansion/contraction, natural selection, and mutation/recombination rates.
- Studying the genetic architecture of complex traits and detecting disease-causing variation in the human genome (e.g., heritability, polygenic prediction, association, fine-mapping).
Jan 9, 2025
New paper on Quickdraws, “A scalable variational inference approach for increased mixed-model association power”, published in Nature Genetics.
The Quickdraws software is availble here, summary statistics are available here.
Nov 29, 2024
New collaborative papers on ancient DNA analysis of early farmers of central Europe (Gelabert et al. Nature Human Behaviour, news coverage) and on Genomics England genotype imputation of the UK Biobank (Shi et al. Nature Genetics); preprints on the genetic origins of the Indo-Europeans (Lazaridis et al. bioRxiv) and on the causes and consequences of DNA repeat expansions (Hujoel et al. bioRxiv).
Nov 23, 2024
Zoi gave a featured plenary talk (15 out of ~3,400 submitted abstracts) on inferring genealogical relationships between ancient and modern genomes at the American Society of Human Genetics (ASHG 2024) meeting in Denver (CO). She also received a Trainee Research Excellence Award (6 out of ~900 trainee abstracts). Congratulations!
Oct 25, 2024
Pier gave talks at the Society for Molecular Biology and Evolution (SMBE 2024), the PRIMED Consortium, and the Conservation Genomics conference.
Oct 1, 2024
Marius Weidmann (DPhil student), Yining Fan (DPhil student), and Alex Allmont (research software engineer) joined the group.
Aug 4, 2024
Two new preprints from our group: Gunnarsson et al. “A scalable approach for genome-wide inference of ancestral recombination graphs” bioRxiv on the Threads method for fast ARG inference (software here); and Zhu, Kalantzis et al. “Fast variance component analysis using large-scale ancestral recombination graphs” bioRxiv on the ARG-RHE method for ARG-based variance component analysis (software here).
Jun 4, 2024
Pier gave talks at the European Society of Human Genetics (ESHG 2024) meeting, the Machine Learning for Evolutionary Biology conference, and at the Probabilistic Modeling in Genomics (ProbGen 2024) conference, where he chaired a session on ancestral recombination graphs.
Mar 14, 2024
Arni and Romain defended their thesis!
Dec 28, 2023
A new paper on EpiNN, “Genome-wide classification of epigenetic activity reveals regions of enriched heritability in immune-related traits”, was published in Cell Genomics.
Dec 1, 2023
Our paper, “Haplotype-based inference of recent effective population size in modern and ancient DNA samples”, is now published in Nature Communications.
The HapNe-LD and HapNe-IBD programs are available here.