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Verfasst von:Lorenzo Bermejo, Justo [VerfasserIn]   i
 Perez, Alfonso Garcia [VerfasserIn]   i
 Brandt, Andreas [VerfasserIn]   i
 Hemminki, Kari [VerfasserIn]   i
 Matthews, Abigail G. [VerfasserIn]   i
Titel:Comparison of six statistics of genetic association regarding their ability to discriminate between causal variants and genetically linked markers
Verf.angabe:Justo Lorenzo Bermejo, Alfonso Garcia Perez, Andreas Brandt, Kari Hemminki, Abigail G. Matthews
E-Jahr:2011
Jahr:October 19, 2011
Umfang:11 S.
Fussnoten:Gesehen am 17.03.2022
Titel Quelle:Enthalten in: Human heredity
Ort Quelle:Basel : Karger, 1969
Jahr Quelle:2011
Band/Heft Quelle:72(2011), 2, Seite 142-152
ISSN Quelle:1423-0062
Abstract:<i>Objectives:</i> Genome-wide association (GWA) studies still rely on the common-disease common-variant hypothesis since the assumption is associated with increased power. In GWA studies, polymorphisms are genotyped and their association with disease is investigated. Most of the identified associations are indirect and reflect a shared inheritance of the genotyped markers and genetically linked causal variants. We have compared six statistics of genetic association regarding their ability to discriminate between markers and causal susceptibility variants, including a probability value (Pval) and a Bayes Factor (BF) based on logistic regression, and the attributable familial relative risk (FRR). <i>Methods:</i> We carried out a simulation-based sensitivity analysis to explore several conceivable scenarios. Theoretical results were illustrated by established causal associations with age-related macular degeneration and by using imputed data based on HapMap for a case-control study of breast cancer. <i>Results:</i> Our data indicate that a representation of genetic association by FRRs and BFs generally facilitates the distinction of causal variants. The FRR showed the best discriminative power under most investigated scenarios, but no single statistic outperformed the others in all situations. For example, rare moderate- to low-penetrance variants (allele frequency: 1%, dominant odds ratio: ≤2.0) seem to be best discriminated by BFs. <i>Conclusions:</i> Present results may help to fully utilize the data generated in association studies that take advantage of next generation sequencing and/or multiple imputation based on the 1000 Genomes Project.
DOI:doi:10.1159/000332006
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext: https://doi.org/10.1159/000332006
 Volltext: https://www.karger.com/Article/FullText/332006
 DOI: https://doi.org/10.1159/000332006
Datenträger:Online-Ressource
Sprache:eng
K10plus-PPN:1795984635
Verknüpfungen:→ Zeitschrift

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