Imperial College London
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Professor Sarah Fidler BSc. MBBS. FRCP. PhD

Faculty of Medicine, Department of Infectious Disease

Professor of HIV and Communicable Diseases
 
 
 
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Contact

 

+44 (0)20 7594 6230s.fidler

 
 
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Location

 

clinical trial centre Winston Churchill wingMedical SchoolSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@unpublished{Palmer:2017:10.1101/155242,
author = {Palmer, DS and Turner, I and Fidler, S and Frater, J and Goulder, P and Goedhals, D and Huang, K-HG and Oxenius, A and Phillips, R and Shapiro, R and van, Vuuren C and McLean, AR and McVean, G},
doi = {10.1101/155242},
title = {Mapping the drivers of within-host pathogen evolution using massive data sets},
url = {http://dx.doi.org/10.1101/155242},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - UNPB
AB  - <jats:title>Abstract</jats:title><jats:p>Differences among hosts, resulting from genetic variation in the immune system or heterogeneity in drug treatment, can impact within-host pathogen evolution. Identifying such interactions can potentially be achieved through genetic association studies. However, extensive and correlated genetic population structure in hosts and pathogens presents a substantial risk of confounding analyses. Moreover, the multiple testing burden of interaction scanning can potentially limit power. To address these problems, we have developed a Bayesian approach for detecting host influences on pathogen evolution that makes use of vast existing data sets of pathogen diversity to improve power and control for stratification. The approach models key processes, including recombination and selection, and identifies regions of the pathogen genome affected by host factors. Using simulations and empirical analysis of drug-induced selection on the HIV-1 genome we demonstrate the power of the method to recover known associations and show greatly improved precision-recall characteristics compared to other approaches. We build a high-resolution map of HLA-induced selection in the HIV-1 genome, identifying novel epitope-allele combinations.</jats:p>
AU  - Palmer,DS
AU  - Turner,I
AU  - Fidler,S
AU  - Frater,J
AU  - Goulder,P
AU  - Goedhals,D
AU  - Huang,K-HG
AU  - Oxenius,A
AU  - Phillips,R
AU  - Shapiro,R
AU  - van,Vuuren C
AU  - McLean,AR
AU  - McVean,G
DO  - 10.1101/155242
PY  - 2017///
TI  - Mapping the drivers of within-host pathogen evolution using massive data sets
UR  - http://dx.doi.org/10.1101/155242
ER  -
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