Announcing ProbGen22 in Oxford 28-30 March

The organizing committee is pleased to announce the 7th Probabilistic Modeling in Genomics Conference (ProbGen22) to be held at the Blavatnik School of Government and Somerville College Oxford from 28th-30th March 2022.

The meeting will be a hybrid in-person and online event. Talk sessions will feature live speakers, both in-person and online, and will take place during the afternoons (making live attendance feasible for US timezones). Talks will be recorded and made available to registrants for a period of one month. Poster sessions will be held online during the evenings.

The conference will cover probabilistic models, algorithms, and statistical methods across a broad range of applications in genetics and genomics. We invite abstract submissions on a range of topics including population genetics, natural selection, Quantitative genetics, Methods for GWAS, Applications to cancer and other diseases, Causal inference in genetic studies, Functional genomics, Assembly and variant identification, Phylogenetics, Single cell 'omics, Deep learning in genomics and Pathogen genomics.

The registration deadline is 28th February 2022.

For more details visit the conference website. 

Postdoc Available in Statistical Genetics

The closing date for applications for this post is noon on Wednesday 15th April 2020.

We are seeking an exceptional researcher with a track record in methods development for Statistical Genomics and an interest in Infectious Disease to join our group at the Big Data Institute. Our research focuses on Bacterial Genomics, Genome-Wide Association Studies and Population Genetics. The aim of the post is to conduct innovative research within the group's range of interests and to make use of the opportunities afforded by our outstanding collaborators. We welcome candidates who wish to use the opportunity as a stepping stone to independent funding.

The Oxford University Big Data Institute (BDI) is an interdisciplinary research centre aiming to develop, evaluate and deploy efficient methods for acquiring and analysing biomedical data at scale and for exploiting the opportunities arising from such studies. The Nuffield Department of Population Health, a partner in the BDI, contains world-renowned population health research groups and is an excellent environment for multi-disciplinary teaching and research.

The Postdoctoral Researcher in Statistical Genomics will join our team which has expertise in microbiology, genomics, evolution, population genetics and statistical inference. Responsibilities include planning a research project and milestones with help and guidance from the group, preparing manuscripts for publication, keeping records of results and methods and tracking milestones, and disseminating results.

To be considered, you need to hold, or be close to completion of, a PhD/DPhil involving statistical methods development. You also need experience of large-scale statistical data analysis, evidence of originating and executing your own academic research ideas and excellent interpersonal skills and the ability to work closely with others in a team.

For informal enquiries, please contact me.

Further details, including how to apply are here: https://my.corehr.com/pls/uoxrecruit/erq_jobspec_details_form.jobspec?p_id=145506

Postdoctoral Scientist in Statistical Genomics

We are recruiting for a Postdoctoral Scientist in Statistical Genomics working on Antimicrobial Resistance (AMR) gene discovery and focused on Tuberculosis. This will be a joint position at the University of Oxford between Derrick Crook's group and mine, and part of the large international CRyPTIC consortium.

The role is for a population geneticist or statistical geneticist to develop and apply statistical methods, including genome-wide association studies, for discovering rare and common genetic variants underlying antimicrobial resistance in Mycobacterium tuberculosis.

One third of the world's population - 2.5 billion people - are thought to be infected with tuberculosis (TB). This post offers an opportunity to work with global TB experts from five continents, statistical geneticists, clinicians, medical statisticians and software engineers; integrating statistical genetics, bioinformatics and machine learning methods with the aim of uncovering all genomic variants causing at least 1% resistance to first line anti-TB drugs.

We're looking for candidates with a PhD in genomics, evolutionary biology, statistics or a related subject. The post is full-time and fixed-term for up to 3 years initially.

The deadline for applications is noon on Friday 6th May 2016.

PLoS Pathogens Review Published!

Published today in PLoS Pathogens:

New method inferring natural selection published today

I am pleased to report that my new paper "A population genetics-phylogenetics approach to inferring natural selection" is published today in PLoS Genetics. This is the culmination of two years work at the University of Chicago with Molly Przeworski, plus a good deal of follow-up since I moved to Oxford. In the paper we introduce a new way of combining population genetics and phylogenetics models of natural selection, and a statistical method (gammaMap) for estimating parameters under the model. From a collection of sequences within one or more species - in the paper, we use 100 X-linked coding sequences that Peter Andolfatto produced in Drosophila melanogaster and D. simulans - the method allows you to estimate the distribution of fitness effects within each lineage, and localize the signal of selection using a Bayesian sliding window approach. Using Ryan Hernandez's simulator SFSCODE we tested the method for robustness to demographic change and linkage disequilbrium, and we investigated the effect that common assumptions concerning spatial variation in selection coefficients (sitewise, genewise and sliding window approaches) have on inference of selection. During the winter break I will work on compiling the program for different platforms and writing the documentation, with a view to releasing the software early in the New Year. Subscribe to this blog for updates or - if you are too impatient to wait - send me an email.