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A quick and simple method for detecting subjects with abnormal genetic background in case-control samples

Published online by Cambridge University Press:  31 July 2002

D. CURTIS
Affiliation:
Joint Academic Department of Psychological Medicine, St Bartholomew's and Royal London School of Medicine and Dentistry, 3rd Floor Outpatient Building, Royal London Hospital, Whitechapel, London E1 1BB, UK
B. V. NORTH
Affiliation:
Joint Academic Department of Psychological Medicine, St Bartholomew's and Royal London School of Medicine and Dentistry, 3rd Floor Outpatient Building, Royal London Hospital, Whitechapel, London E1 1BB, UK
H. M. D. GURLING
Affiliation:
Molecular Psychiatry Laboratory, Windeyer Institute of Medical Sciences, Department of Psychiatry and Behavioural Sciences, Royal Free and University College Medical School, University College London, 46 Cleveland St. London W1T 4JF, UK
E. BLAVERI
Affiliation:
Molecular Psychiatry Laboratory, Windeyer Institute of Medical Sciences, Department of Psychiatry and Behavioural Sciences, Royal Free and University College Medical School, University College London, 46 Cleveland St. London W1T 4JF, UK
P. C. SHAM
Affiliation:
Department of Psychological Medicine, Institute of Psychiatry, De Crespigny Park, London SE5 8AF, UK
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Abstract

It is important that case-control samples be drawn from a genetically homogeneous population in order to avoid artefactual false positive results and to enhance power to detect disease mutations and markers in linkage disequilibrium with them. Tests which simply compare overall marker allele frequencies between cases and controls will fail to identify a relatively small number of subjects drawn from a different genetic background who could usefully be discarded from the sample. Such subjects can be identified using multilocus tests, but previously described tests have been unnecessarily complex and cumbersome for this simple application. We describe a straightforward test, implemented in the CHECKHET program, which uses a measure of genetic difference and permutation procedures to rapidly identify such subjects using genotypes from multiple unlinked markers. It seems to perform reasonably well on simulated data, and with real data appears to identify two abnormal subjects within a case-control sample. We recommend that such tests be routinely applied to case-control samples once sufficient numbers of markers have been genotyped within them.

Type
Research Article
Copyright
University College London 2002

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