The DOI matches its Crossref record; 102 of the 102 references it cites were found in a registry or an index.
Statistical power and significance testing in large-scale genetic studies
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.
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“Given the promise of molecular systems and integrative network approaches, it is perhaps surprising that there are few universally agreed on metrics, power analysis tools or methodological comparisons to guide experimental design, execution and analysis, such as there are for genetic association studies172.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [172]
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Finding the genomic basis of local adaptation: pitfalls, practical solutions, and future directions
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“The result is a distribution of P values or test statistics for that data set, and many of the identi fi ed loci will be false positives if multiple testing is not corrected for (Sham and Purcell 2014).”
Advancing the understanding of autism disease mechanisms through genetics
de la Torre-Ubieta, L., Won, H., Stein, J. L., & Geschwind, D. H. (2016) · Nature Medicine · doi:10.1038/nm.4071 · Cited by 827
Metadata
- Authors
- Sham, P. C., & Purcell, S. M.
- Affiliations
- University of Hong Kong (HK)
- Massachusetts General Hospital (US)
- Corresponding author
- Sham, Pak C.
- Venue
- Nature Reviews Genetics
- Published
- 2014-04-17
- Volume
- 15
- Issue
- 5
- Pages
- 335-346
- ISSN
- 1471-0056 (ISSN-L)
- 1471-0064
- OpenAlex
- W2116514399
- Cited by
- 573
- References
- 102
- Citations by year
- 2026: 23 · 2025: 26 · 2024: 22 · 2023: 50 · 2022: 28 · 2021: 40 · 2020: 54 · 2019: 58 · 2018: 73 · 2017: 77 · 2016: 65 · 2015: 45 · 2014: 11
- FWCI
- 8.75
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Reviews Genetics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Mental Health (R01MH099126)
- National Human Genome Research Institute (R01HG005827)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Keywords
- statistical power, significance testing, multiple testing correction, rare variants, genome-wide association study, exome sequencing, significance threshold, research design
- MeSH terms
- Data Interpretation, Statistical, Gene Frequency, Genetic Testing, Genotype, Humans, Case-Control Studies, Sequence Analysis, DNA, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Genome-Wide Association Study
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