Cited by 15Genetic Associations and EpidemiologyForensic and Genetic ResearchGenetic Mapping and Diversity in Plants and Animals

Using ancestry matching to combine family-based and unrelated samples for genome-wide association studies

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Crossett, Andrew, Kent, Brian P., Klei, Lambertus, Ringquist, Steven, Trucco, Massimo, Roeder, Kathryn, Devlin, Bernie·2010·Statistics in Medicine

Abstract

We propose a method to analyze family‐based samples together with unrelated cases and controls. The method builds on the idea of matched case–control analysis using conditional logistic regression (CLR). For each trio within the family, a case (the proband) and matched pseudo‐controls are constructed, based upon the transmitted and untransmitted alleles. Unrelated controls, matched by genetic ancestry, supplement the sample of pseudo‐controls; likewise unrelated cases are also paired with genetically matched controls. Within each matched stratum, the case genotype is contrasted with control/pseudo‐control genotypes via CLR, using a method we call matched‐CLR (mCLR). Eigenanalysis of numerous SNP genotypes provides a tool for mapping genetic ancestry. The result of such an analysis can be thought of as a multidimensional map, or eigenmap, in which the relative genetic similarities and differences amongst individuals is encoded in the map. Once constructed, new individuals can be projected onto the ancestry map based on their genotypes. Successful differentiation of individuals of distinct ancestry depends on having a diverse, yet representative sample from which to construct the ancestry map. Once samples are well‐matched, mCLR yields comparable power to competing methods while ensuring excellent control over Type I error. Copyright © 2010 John Wiley & Sons, Ltd.

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  • No evidence was found for unusual ancestral clustering in parents of probands with 16p11.2 or 7q11.23 CNVs.

    “We found no evidence for this.”
  • The method to analyze control and family-based data builds on two related ideas: matched case-control analysis using conditional logistic regression and the natural connection between family-based analysis and conditional logistic regression of alleles found in probands and matched pseudo-controls.

    “The method to analyze control and family-based data (49) builds on two related ideas: matched case–control analysis using conditional logistic regression (e.g. 52) and the natural connection between family-based analysis and conditional logistic regression of alleles found in probands (the transmitted alleles) and matched pseudo-controls (formed from transmitted and un-transmitted alleles) (49).”

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  1. [39]Huber P The behaviour of maximum likelihood estimates under non-standard conditions. Proceedings of the Fifth Berkeley Symposium in Mathematical Statistics and Probability 1967 1 221 233

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Authors
Crossett, A., Kent, B. P., Klei, L., Ringquist, S., Trucco, M., Roeder, K., & Devlin, B.
Affiliations
  • Carnegie Mellon University (US)
  • University of Pittsburgh (US)
  • Children's Hospital of Pittsburgh (US)
Corresponding author
Roeder, Kathryn
Venue
Statistics in Medicine
Publisher
Wiley
Published
2010-09-22
Volume
29
Issue
28
Pages
2932-2945
ISSN
  • 0277-6715 (ISSN-L)
  • 1097-0258
OpenAlex
W2134071364
Cited by
15
References
48
Citations by year
2022: 1 · 2021: 2 · 2019: 1 · 2016: 1 · 2015: 1 · 2014: 2 · 2012: 1
FWCI
1.26
Type
journal article
Language
en
Open access
Locations
  • Statistics in Medicine (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • U.S. Department of Defense
  • Autism Speaks (AS7462)
  • National Institutes of Health
  • Office of Naval Research
  • National Institute of Mental Health (R37MH057881, R01MH057881, MH057881)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
Keywords
family-based association, matched case-control analysis, conditional logistic regression, trio analysis, genome-wide association study, type I error control
MeSH terms
Diabetes Mellitus, Type 1, Family, Female, HLA Antigens, Humans, Male, Pedigree, Models, Statistical, Logistic Models, Case-Control Studies, Polymorphism, Single Nucleotide, Racial Groups, Genome-Wide Association Study, Biostatistics

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