Kelleher J, Wong Y, Wohns AW, Fadil C, Albers PK, McVean G.
Nature Genetics, (2019) pg 1330-1338
Inferring the full genealogical history of a set of DNA sequences is a core problem in evolutionary biology, because this history encodes information about the events and forces that have influenced a species. However, current methods are limited, and the most accurate techniques are able to process no more than a hundred samples. As datasets that consist of millions of genomes are now being collected, there is a need for scalable and efficient inference methods to fully utilize these resources. Here we introduce an algorithm that is able to not only infer whole-genome histories with comparable accuracy to the state-of-the-art but also process four orders of magnitude more sequences. The approach also provides an ‘evolutionary encoding’ of the data, enabling efficient calculation of relevant statistics. We apply the method to human data from the 1000 Genomes Project, Simons Genome Diversity Project and UK Biobank, showing that the inferred genealogies are rich in biological signal and efficient to process.
A Multi-tissue Transcriptome Analysis of Human Metabolites Guides Interpretability of Associations Based on Multi-SNP Models for Gene Expression.
23 January 2020
Ndungu A, Payne A, Torres JM, van de Bunt M, McCarthy MI. American Journal of Human Genetics, (2020) pg 188-201 Abstract There is particular interest in transcriptome-wide association studies...
A pathology benchmarking tool to improve patient care by giving GPs simple, actionable insights
16 April 2019
OpenPathology is a new project being built by the EBM DataLab at the University of Oxford, supported by HDR UK. This repo is the code related to the website at https://openpathology.net. The code...
The potential for improving cardio-renal outcomes by sodium-glucose co-transporter-2 inhibition in people with chronic kidney disease: a rationale for the EMPA-KIDNEY study
25 October 2018
Herrington WG, Preiss D, Haynes R, von Eynatten M, Staplin N, Hauske SJ, George JT, Green JB, Landray MJ, Baigent C, Wanner C Clinical Kidney Journal (2019) 11(6):749–761 Diabetes is a common...