title: Estimating the number of true discoveries in genome-wide association studies.
abstract: Recent genome-wide association studies have reported the discoveries of genetic variants of small to moderate effects. However, most studies of complex diseases face a great challenge because the number of significant variants is less than what is required to explain the disease heritability. A new approach is needed to recognize all potential discoveries in the data. In this paper, we present a practical model-free procedure to estimate the number of true discoveries as a function of the number of top-ranking SNPs together with the confidence bounds. This approach allows a practical methodology of general utility and produces relevant statistical quantities with simple interpretation.
authors: Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, 17177, Sweden.
authors: Woojoo
authors: W
authors: Lee
authors: A
authors: A
authors: Gusnanto
authors: A
authors: A
authors: Salim
authors: P
authors: P
authors: Magnusson
authors: Xueling
authors: X
authors: Sim
authors: E S
authors: ES
authors: Tai
authors: Y
authors: Y
authors: Pawitan
mesh_terms: D044466:Asian People / Q000235:genetics / Q000706:statistics & numerical data; D008076:Cholesterol, HDL / Q000097:blood / Q000235:genetics; D003198:Computer Simulation / Q000706:statistics & numerical data; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D005189:False Positive Reactions; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study / Q000706:statistics & numerical data*; D006801:Humans; D008268:Macular Degeneration / Q000453:epidemiology / Q000235:genetics; D008432:Mathematical Computing; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide; D012559:Schizophrenia / Q000453:epidemiology / Q000235:genetics; D012846:Singapore / Q000453:epidemiology
chemical_list: D008076:Cholesterol, HDL