Correcting for Population Stratification Reduces False Positive and False Negative Results in Joint Analyses of Host and Pathogen Genomes.

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Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_74507151A9A8
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Correcting for Population Stratification Reduces False Positive and False Negative Results in Joint Analyses of Host and Pathogen Genomes.
Journal
Frontiers in genetics
Author(s)
Naret O., Chaturvedi N., Bartha I., Hammer C., Fellay J.
Working group(s)
Swiss HIV Cohort Study (SHCS)
ISSN
1664-8021 (Print)
ISSN-L
1664-8021
Publication state
Published
Issued date
2018
Peer-reviewed
Oui
Volume
9
Pages
266
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
Studies of host genetic determinants of pathogen sequence variations can identify sites of genomic conflicts, by highlighting variants that are implicated in immune response on the host side and adaptive escape on the pathogen side. However, systematic genetic differences in host and pathogen populations can lead to inflated type I (false positive) and type II (false negative) error rates in genome-wide association analyses. Here, we demonstrate through a simulation that correcting for both host and pathogen stratification reduces spurious signals and increases power to detect real associations in a variety of tested scenarios. We confirm the validity of the simulations by showing comparable results in an analysis of paired human and HIV genomes.
Keywords
escape variants, genome-wide association study, host-pathogen genomics, population stratification, simulation study
Pubmed
Web of science
Open Access
Yes
Create date
13/09/2020 14:39
Last modification date
09/04/2024 7:14
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