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external supervisor

Azim Ansari, Nuffield Department of Medicine

Background

Infection is fundamentally an interaction between human and pathogen. There is long-standing interest in the role of human-pathogen genetic interactions in infection traits, including severity and outcome. A major challenge is devising sensitive analyses robust to false positives.

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

This project aims to develop and apply computational tools for performing trillions of association tests between millions of human and millions of pathogen genetic variants, while controlling the false positive rate without loss of statistical power. Using published and new data generated in-house, we will apply the harmonic mean p-value method (PMID:30610179) to this problem. Depending on the student, we can focus more on theory or applications, and address related problems like epistasis.

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING

Training in statistical genetics will be acquired from colleagues including members of the Modernising Medical Microbiology consortium. University courses are available in R, python and scientific computing.

PROSPECTIVE STUDENT

This project would suit numerically fluent biologists or physical/mathematical scientists with knowledge of statistics, genetics and programming.

Supervisors