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The Limits of Individual Identification from Sample Allele Frequencies: Theory and Statistical Analysis

It was shown recently using experimental data that it is possible under certain conditions to determine whether a person with known genotypes at a number of markers was part of a sample from which only allele frequencies are known. Using population genetic and statistical theory, we show that the po...

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Detalles Bibliográficos
Autores principales: Visscher, Peter M., Hill, William G.
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2746319/
https://www.ncbi.nlm.nih.gov/pubmed/19798439
http://dx.doi.org/10.1371/journal.pgen.1000628
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author Visscher, Peter M.
Hill, William G.
author_facet Visscher, Peter M.
Hill, William G.
author_sort Visscher, Peter M.
collection PubMed
description It was shown recently using experimental data that it is possible under certain conditions to determine whether a person with known genotypes at a number of markers was part of a sample from which only allele frequencies are known. Using population genetic and statistical theory, we show that the power of such identification is, approximately, proportional to the number of independent SNPs divided by the size of the sample from which the allele frequencies are available. We quantify the limits of identification and propose likelihood and regression analysis methods for the analysis of data. We show that these methods have similar statistical properties and have more desirable properties, in terms of type-I error rate and statistical power, than test statistics suggested in the literature.
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spelling pubmed-27463192009-10-02 The Limits of Individual Identification from Sample Allele Frequencies: Theory and Statistical Analysis Visscher, Peter M. Hill, William G. PLoS Genet Research Article It was shown recently using experimental data that it is possible under certain conditions to determine whether a person with known genotypes at a number of markers was part of a sample from which only allele frequencies are known. Using population genetic and statistical theory, we show that the power of such identification is, approximately, proportional to the number of independent SNPs divided by the size of the sample from which the allele frequencies are available. We quantify the limits of identification and propose likelihood and regression analysis methods for the analysis of data. We show that these methods have similar statistical properties and have more desirable properties, in terms of type-I error rate and statistical power, than test statistics suggested in the literature. Public Library of Science 2009-10-02 /pmc/articles/PMC2746319/ /pubmed/19798439 http://dx.doi.org/10.1371/journal.pgen.1000628 Text en Visscher, Hill. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Visscher, Peter M.
Hill, William G.
The Limits of Individual Identification from Sample Allele Frequencies: Theory and Statistical Analysis
title The Limits of Individual Identification from Sample Allele Frequencies: Theory and Statistical Analysis
title_full The Limits of Individual Identification from Sample Allele Frequencies: Theory and Statistical Analysis
title_fullStr The Limits of Individual Identification from Sample Allele Frequencies: Theory and Statistical Analysis
title_full_unstemmed The Limits of Individual Identification from Sample Allele Frequencies: Theory and Statistical Analysis
title_short The Limits of Individual Identification from Sample Allele Frequencies: Theory and Statistical Analysis
title_sort limits of individual identification from sample allele frequencies: theory and statistical analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2746319/
https://www.ncbi.nlm.nih.gov/pubmed/19798439
http://dx.doi.org/10.1371/journal.pgen.1000628
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