Selection of Influential Genetic Markers Among a Large Number of Candidates Based on Effect Estimation Rather than Hypothesis Testing: An Approach for Genome-Wide Association Studies.
Author
Summary, in English
In epidemiologic studies on direct genetic associations, hypothesis testing is primarily considered for evaluating the effects of each candidate genetic marker, eg, single nucleotide polymorphisms. To help investigators protect themselves from over-interpreting statistically significant findings that are not likely to signify a true effect-a problem connected to multiple comparisons-consideration of the false-positive report probability has been proposed. There have also been arguments advocating estimation of effect size rather than hypothesis testing (P value). Here, we propose an estimation-based approach that offers an attractive alternative to the test-based false-positive report probability, when the task is to select promising genetic markers for further analyses. We discuss the potential of this estimation-based approach for genome-wide association studies.
Department/s
Publishing year
2008
Language
English
Pages
302-308
Publication/Series
Epidemiology
Volume
19
Links
Document type
Journal article
Publisher
Wolters Kluwer
Topic
- Public Health, Global Health, Social Medicine and Epidemiology
Status
Published
ISBN/ISSN/Other
- ISSN: 1531-5487