Literature DB >> 19799556

Identifying individuals in a complex mixture of DNA with unknown ancestry.

Joshua Sampson1, Hongyu Zhao.   

Abstract

A new test was recently developed that could use a high-density set of single nucleotide polymorphisms (SNPs) to determine whether a specific individual contributed to a mixture of DNA. The test statistic compared the genotype for the individual to the allele frequencies in the mixture and to the allele frequencies in a reference group. This test requires the ancestries of the reference group to be nearly identical to those of the contributors to the mixture. Here, we first quantify the bias, the increase in type I and type II error, when the ancestries are not well matched. Then, we show that the test can also be biased if the number of subjects in the two groups differ or if the platforms used to measure SNP intensities differ. We then introduce a new test statistic and a test that only requires the ancestries of the reference group to be similar to the individual of interest, and show that this test is not only robust to the number of subjects and platform, but also has increased power of detection. The two tests are compared on both HapMap and simulated data.

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Year:  2009        PMID: 19799556      PMCID: PMC2861329          DOI: 10.2202/1544-6115.1469

Source DB:  PubMed          Journal:  Stat Appl Genet Mol Biol        ISSN: 1544-6115


  10 in total

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2.  Evaluating mixed stains with contributors of different ethnic groups under the NRC-II Recommendation 4.1.

Authors:  Wing K Fung; Yue-Qing Hu
Journal:  Stat Med       Date:  2002-12-15       Impact factor: 2.373

3.  The International HapMap Project.

Authors: 
Journal:  Nature       Date:  2003-12-18       Impact factor: 49.962

Review 4.  Encoded evidence: DNA in forensic analysis.

Authors:  Mark A Jobling; Peter Gill
Journal:  Nat Rev Genet       Date:  2004-10       Impact factor: 53.242

5.  Developing a SNP panel for forensic identification of individuals.

Authors:  Kenneth K Kidd; Andrew J Pakstis; William C Speed; Elena L Grigorenko; Sylvester L B Kajuna; Nganyirwa J Karoma; Selemani Kungulilo; Jong-Jin Kim; Ru-Band Lu; Adekunle Odunsi; Friday Okonofua; Josef Parnas; Leslie O Schulz; Olga V Zhukova; Judith R Kidd
Journal:  Forensic Sci Int       Date:  2005-12-19       Impact factor: 2.395

6.  Identification of the genetic basis for complex disorders by use of pooling-based genomewide single-nucleotide-polymorphism association studies.

Authors:  John V Pearson; Matthew J Huentelman; Rebecca F Halperin; Waibhav D Tembe; Stacey Melquist; Nils Homer; Marcel Brun; Szabolcs Szelinger; Keith D Coon; Victoria L Zismann; Jennifer A Webster; Thomas Beach; Sigrid B Sando; Jan O Aasly; Reinhard Heun; Frank Jessen; Heike Kolsch; Magdalini Tsolaki; Makrina Daniilidou; Eric M Reiman; Andreas Papassotiropoulos; Michael L Hutton; Dietrich A Stephan; David W Craig
Journal:  Am J Hum Genet       Date:  2006-12-06       Impact factor: 11.025

7.  Genetic privacy. Whole-genome data not anonymous, challenging assumptions.

Authors:  Jennifer Couzin
Journal:  Science       Date:  2008-09-05       Impact factor: 47.728

8.  Population variation of human mtDNA control region sequences detected by enzymatic amplification and sequence-specific oligonucleotide probes.

Authors:  M Stoneking; D Hedgecock; R G Higuchi; L Vigilant; H A Erlich
Journal:  Am J Hum Genet       Date:  1991-02       Impact factor: 11.025

9.  Resolving individuals contributing trace amounts of DNA to highly complex mixtures using high-density SNP genotyping microarrays.

Authors:  Nils Homer; Szabolcs Szelinger; Margot Redman; David Duggan; Waibhav Tembe; Jill Muehling; John V Pearson; Dietrich A Stephan; Stanley F Nelson; David W Craig
Journal:  PLoS Genet       Date:  2008-08-29       Impact factor: 5.917

10.  Highly cost-efficient genome-wide association studies using DNA pools and dense SNP arrays.

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  10 in total
  2 in total

Review 1.  Assessing and managing risk when sharing aggregate genetic variant data.

Authors:  David W Craig; Robert M Goor; Zhenyuan Wang; Justin Paschall; Jim Ostell; Michael Feolo; Stephen T Sherry; Teri A Manolio
Journal:  Nat Rev Genet       Date:  2011-09-16       Impact factor: 53.242

2.  Participant identification in genetic association studies: improved methods and practical implications.

Authors:  Nicholas Masca; Paul R Burton; Nuala A Sheehan
Journal:  Int J Epidemiol       Date:  2011-12       Impact factor: 7.196

  2 in total

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