| Affiliation: | 1. Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul, South Korea;2. Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts;3. Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts;4. Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts |
| Abstract: | Proportions of false-positive rates in genome-wide association analysis are affected by population stratification, and if it is not correctly adjusted, the statistical analysis can produce the large false-negative finding. Therefore various approaches have been proposed to adjust such problems in genome-wide association studies. However, in spite of its importance, a few studies have been conducted in genome-wide single nucleotide polymorphism (SNP)-by-environment interaction studies. In this report, we illustrate in which scenarios can lead to the false-positive rates in association mapping and approach to maintaining the overall type-1 error rate. |
