Estimation of the multiple testing burden for genomewide association studies of nearly all common variants
Columbia University · Massachusetts General Hospital · +4 more institutions
Abstract
Genomewide association studies are an exciting strategy in genetics, recently becoming feasible and harvesting many novel genes linked to multiple phenotypes. Determining the significance of results in the face of testing a genomewide set of multiple hypotheses, most of which are producing noisy, null-distributed association signals, presents a challenge to the wide community of association researchers. Rather than each study engaging in independent evaluation of significance standards, we have undertaken the task of developing such standards for genomewide significance, based on data collected by the International Haplotype Map Consortium. We report an estimated testing burden of a million independent tests…
Citation impact
- FWCI
- 35.64
- Percentile
- 100%
- References
- 24
Authors
4- IPItsik Pe’er
Columbia University
- RYRoman Yelensky
Massachusetts General Hospital, Harvard–MIT Division of Health Sciences and Technology, Center for Human Genetics
- DADavid Altshuler
Broad Institute, Harvard University, Massachusetts General Hospital, Center for Human Genetics
- MJMark J. DalyCorresponding
Harvard University, Massachusetts General Hospital, Center for Human Genetics
Topics & keywords
- Multiple comparisons problem
- Genetic association
- Null hypothesis
- Statistical hypothesis testing
- Biology
- Computational biology
- Genetics
- Association (psychology)