A new statistic and its power to infer membership and phenotype in a genome-wide association study using genotype frequencies
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Summary
Using a likelihood-based statistical framework, an improved statistic is developed that uses genotype frequencies and individual genotypes to infer whether a specific individual or any close relatives participated in the GWAS and, if so, what the participant's phenotype status is.
- Type
- article
- Published
- 2009-10-04
- Cited by
- 56
- References
- 7
- OpenAlex
- https://openalex.org/W2073027025
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:14873428
Keywords
Genome-wide association study, Statistic, Biology, Genotype, Statistical power
References
- Genome-wide association studies: theoretical and practical concerns
- Resolving Individuals Contributing Trace Amounts of DNA to Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays
- Genome-wide association studies for complex traits: consensus, uncertainty and challenges
- The Wellcome Trust Case Control Consortium, U.K.
- A HapMap harvest of insights into the genetics of common disease.
- The NCBI dbGaP database of genotypes and phenotypes
- Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls
Cited by
- Is the NIH policy for sharing GWAS data running the risk of being counterproductive?
- Cancer gene sequencing: ethical challenges and promises.
- Privacy, Confidentiality, and Health Research
- The Genotype-Tissue Expression (GTEx) project
- Privacy and Security in the Genomic Era
- Privacy Risks from Genomic Data-Sharing Beacons
- Response to Knoppers et al.
- Routes for breaching and protecting genetic privacy
- Confronting Real Time Ethical, Legal, and Social Issues in the eMERGE (Electronic Medical Records and Genomics) Consortium
- Genomics, Biobanks, and the Trade-Secret Model
- Complex mixtures: a critical examination of a paper by Homer et al.
- A study of the efficiency of pooling in haplotype estimation
- Sharing clinical trial data: maximizing benefits, minimizing risk.
- Potential for revealing individual-level information in genome-wide association studies.
- Not so lost in the genetic crowd
- Overcoming the obstacles to returning genomic research results.
- Reporting Actionable Research Results: Shared Secrets Can Save Lives
- Genetic studies of SH3PXD2B and its contributions to ocular diseases
- Methods for the de-identification of electronic health records for genomic research
- Ethical, legal, and counseling challenges surrounding the return of genetic results in oncology.
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