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Detecting Pedigree Relationship Errors

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Statistical Human Genetics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1666))

Abstract

Pedigree relationship errors often occur in family data collected for genetic studies, and unidentified errors can lead to either increased false positives or decreased power in both linkage and association analyses. Here, we review several allele sharing as well as likelihood-based statistics that were proposed to efficiently extract genealogical information from available genome-wide marker data, and the software package PREST that implements these methods. We provide the detailed analytical steps involved using two application examples, and we discuss various practical issues, including result interpretation.

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References

  1. Boehnke M, Cox NJ (1997) Accurate inference of relationships in sib-pair linkage studies. Am J Hum Genet 61(2):423–429

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Voight BF, Pritchard JK (2005) Confounding from cryptic relatedness in case-control association studies. PLoS Genet 1(3):e32

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Thornton T, McPeek MS (2010) Roadtrips: case-control association testing with partially or completely unknown population and pedigree structure. Am J Hum Genet 86(2):172–184

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Goring HH, Ott J (1997) Relationship estimation in affected sib pair analysis of late-onset diseases. Eur J Hum Genet 5(2):69–77

    PubMed  CAS  Google Scholar 

  5. O'Connell JR, Weeks DE (1998) Pedcheck: a program for identification of genotype incompatibilities in linkage analysis. Am J Hum Genet 63(1):259–266

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Ehm M, Wagner M (1998) A test statistic to detect errors in sib-pair relationships. Am J Hum Genet 62(1):181–188

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. McPeek MS, Sun L (2000) Statistical tests for detection of misspecified relationships by use of genome-screen data. Am J Hum Genet 66(3):1076–1094

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Abecasis GR, Cherny SS, Cookson WO, Cardon LR (2001) Grr: graphical representation of relationship errors. Bioinformatics 17(8):742–743

    Article  CAS  PubMed  Google Scholar 

  9. Sieberts SK, Wijsman EM, Thompson EA (2002) Relationship inference from trios of individuals, in the presence of typing error. Am J Hum Genet 70(1):170–180

    Article  CAS  PubMed  Google Scholar 

  10. Sun L, Wilder K, McPeek MS (2002) Enhanced pedigree error detection. Hum Hered 54(2):99–110

    Article  PubMed  Google Scholar 

  11. Rabiner L (1989) A tutorial on hidden Markov models and selected applications in speech recognition. Proc IEEE 77(2):257–286

    Article  Google Scholar 

  12. Sun L (2001) Two statistical problems in human genetics. University of Chicago, PhD thesis

    Google Scholar 

  13. Thompson EA (1975) The estimation of pairwise relationships. Ann Hum Genet 39(2):173–188

    Article  CAS  PubMed  Google Scholar 

  14. Thompson EA (1986) Pedigree analysis in human genetics. The Johns Hopkins University Press, Baltimore

    Google Scholar 

  15. Dimitromanolakis A, Paterson AD, Sun L (2009) Accurate IBD inference identifies cryptic relatedness in 9 HapMap populations. Abstract #1768 presented at the annual meeting of the American Society of Human Genetics

    Google Scholar 

  16. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PIW, Daly MJ, Sham PC (2007) Plink: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81(3):559–575

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Roy Statist Soc Ser B 57:289–300

    Google Scholar 

  18. Craiu RV, Sun L (2008) Choosing the lesser evil: trade-o_ between false discovery rate and non-discovery rate. Stat Sin 18:861–879

    Google Scholar 

  19. Sun L, Craiu RV, Paterson AD, Bull SB (2006) Stratified false discovery control for large-scale hypothesis testing with application to genome-wide association studies. Genet Epidemiol 30:519–530

    Article  PubMed  Google Scholar 

  20. Manichaikul A, Mychaleckyj JC, Rich SS, Daly K, Sale M, Chen WM (2010) Robust relationship inference in genome-wide association studies. Bioinformatics 56(22):2867–2873

    Article  CAS  Google Scholar 

  21. Chen WM, Manichaikul A, Rich SS (2016) KING 2.0: relationship inference and integrated analysis in one million samples. Abstract #365T presented at the American Society of Human Genetics annual meeting

    Google Scholar 

  22. Begleiter H, Reich T, Nurnberger JJ, Li TK, Conneally PM, Edenberg H, Crowe R, Kuperman S, Schuckit M, Bloom F, Hesselbrock V, Porjesz B, Cloninger CR, Rice J, Goate A (1999) Description of the genetic analysis workshop 11 collaborative study on the genetics of alcoholism. Genet Epidemiol 17(Suppl 1):S25–S30

    Article  PubMed  Google Scholar 

  23. Antoni G, Morange P, Luo Y, Saut N, Burgos G, Heath S, Germain M, Biron-Andreani C, Schved J, Pernod G, Galan P, Zelenika D, Alessi M, Drouet L, Visvikis-Siest S, Wells P, Lathrop M, Emmerich J, Tregouet D, Gagnon F (2010) A multi-stage multi-design strategy provides strong evidence that the bai3 locus is associated with early-onset venous thromboembolism. J Thromb Haemost 8:2671–2679. doi:10.1111/j.1538-7836.2010.04092.x

    Article  PubMed  CAS  Google Scholar 

  24. Epstein MP, Duren WL, Boehnke M (2000) improved inference of relationship for pairs of individuals. Am J Hum Genet 67(5):1219–1231

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. McPeek MS (2002) Inference on pedigree structure from genome screen data. Stat Sin 12:311–335

    Google Scholar 

  26. Sun L, Abney M, McPeek MS (2001) Detection of mis-specified relationships in inbred and outbred pedigrees. Genet Epidemiol 21(Suppl 1):S36–S41

    Article  PubMed  Google Scholar 

  27. Broman KW, Weber JL (1998) Estimation of pairwise relationships in the presence of genotyping errors. Am J Hum Genet 63(5):1563–1564

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Ray A, Weeks DE (2008) Relationship uncertainty linkage statistics (RULS): affected relative pair statistics that model relationship uncertainty. Genet Epidemiol 32(4):313–324

    Article  PubMed  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Statistical Sciences, Faculty of Arts and Science, University of Toronto, 100 St. George Street, Toronto, ON, Canada, M5S 3G3

    Lei Sun

  2. Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, 100 St. George Street, Toronto, ON, Canada, M5S 3G3

    Lei Sun

Authors
  1. Lei Sun
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Corresponding author

Correspondence to Lei Sun .

Editor information

Editors and Affiliations

  1. Case Western Reserve University, Cleveland, OH, USA

    Robert C. Elston

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Sun, L. (2017). Detecting Pedigree Relationship Errors. In: Elston, R. (eds) Statistical Human Genetics. Methods in Molecular Biology, vol 1666. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7274-6_3

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  • DOI: https://doi.org/10.1007/978-1-4939-7274-6_3

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7273-9

  • Online ISBN: 978-1-4939-7274-6

  • eBook Packages: Springer Protocols

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