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Nat Rev Genet. 2014 May;15(5):335-46. doi: 10.1038/nrg3706.

Statistical power and significance testing in large-scale genetic studies.

Author information

1
Centre for Genomic Sciences, Jockey Club Building for Interdisciplinary Research; State Key Laboratory of Brain and Cognitive Sciences, and Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
2
1] Center for Statistical Genetics, Icahn School of Medicine at Mount Sinai, New York 10029-6574, USA. [2] Center for Human Genetic Research, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA.

Abstract

Significance testing was developed as an objective method for summarizing statistical evidence for a hypothesis. It has been widely adopted in genetic studies, including genome-wide association studies and, more recently, exome sequencing studies. However, significance testing in both genome-wide and exome-wide studies must adopt stringent significance thresholds to allow multiple testing, and it is useful only when studies have adequate statistical power, which depends on the characteristics of the phenotype and the putative genetic variant, as well as the study design. Here, we review the principles and applications of significance testing and power calculation, including recently proposed gene-based tests for rare variants.

PMID:
24739678
DOI:
10.1038/nrg3706
[Indexed for MEDLINE]

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