A Bayesian Measure of the Probability of False Discovery in Genetic Epidemiology Studies

• Published in: American journal of human genetics Vol. 81; no. 2; pp. 208 - 227
• Main Author: Wakefield, Jon
• Format: Journal Article
• Language: English
• Published: Chicago, IL Elsevier Inc 01.08.2007; University of Chicago Press; Cell Press; American Society of Human Genetics
• Subjects: Bayes Theorem; Bayesian analysis; Biological and medical sciences; Biostatistics; Data Interpretation, Statistical; Epidemiologic Measurements; Epidemiology; False Positive Reactions; Fundamental and applied biological sciences. Psychology; Gene Frequency; General aspects. Genetic counseling; Genetics; Genetics of eukaryotes. Biological and molecular evolution; Linkage Disequilibrium; Lung cancer; Medical genetics; Medical sciences; Models, Statistical; Molecular and cellular biology; Probability; Human; Genetics; Epidemiology; Probability measure
• ISSN: 0002-9297; 1537-6605
• DOI: 10.1086/519024

In light of the vast amounts of genomic data that are now being generated, we propose a new measure, the Bayesian false-discovery probability (BFDP), for assessing the noteworthiness of an observed association. BFDP shares the ease of calculation of the recently proposed false-positive report probability (FPRP) but uses more information, has a noteworthy threshold defined naturally in terms of the costs of false discovery and nondiscovery, and has a sound methodological foundation. In addition, in a multiple-testing situation, it is straightforward to estimate the expected numbers of false discoveries and false nondiscoveries. We provide an in-depth discussion of FPRP, including a comparison with the q value, and examine the empirical behavior of these measures, along with BFDP, via simulation. Finally, we use BFDP to assess the association between 131 single-nucleotide polymorphisms and lung cancer in a case-control study.