Using ancestry matching to combine family-based and unrelated samples for genome-wide association studies
Open accessAbstract
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.”
From Multiple recurrent de novo CNVs, including duplications of the 7q11.23 Williams syndrome region, are strongly associated with autism (2011) · cites this paper as Crossett et al., 2010
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).”
From A genome-wide scan for common alleles affecting risk for autism (2010) · cites this paper as [49]
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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
- PMC
- PMC4629477
- 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
- green
- www.ncbi.nlm.nih.gov
- 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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