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Selecting cases from nuclear families for case-control association analysis

Moore, R.M.; Pinel, T.; Zhao, J.H.; March, R.; Jawaid, A.; (2005) Selecting cases from nuclear families for case-control association analysis. BMC Genetics , 6 (S1) S105. 10.1186/1471-2156-6-S1-S105. Green open access

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Abstract

We examine the efficiency of a number of schemes to select cases from nuclear families for case-control association analysis using the Genetic Analysis Workshop 14 simulated dataset. We show that with this simulated dataset comparing all affected siblings with unrelated controls is considerably more powerful than all of the other approaches considered. We find that the test statistic is increased by almost 3-fold compared to the next best sampling schemes of selecting all affected sibs only from families with affected parents (AFaff), one affected sib with most evidence of allele-sharing from each family (SF), and all affected sibs from families with evidence for linkage (AFL). We consider accounting for biological relatedness of samples in the association analysis to maintain the correct type I error. We also discuss the relative efficiencies of increasing the ratio of unrelated cases to controls, methods to confirm associations and issues to consider when applying our conclusions to other complex disease datasets.

Type: Article
Title: Selecting cases from nuclear families for case-control association analysis
Open access status: An open access version is available from UCL Discovery
DOI: 10.1186/1471-2156-6-S1-S105
Publisher version: http://dx.doi.org/10.1186/1471-2156-6-S1-S105
Language: English
Additional information: © 2005 Moore et al; licensee BioMed Central Ltd. Article reproduced here under the terms of the Creative Commons Attribution License, see the following web page for more details: (http://creativecommons.org/licenses/by/2.0)
UCL classification: UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Wolfson Inst for Biomedical Research
URI: https://discovery.ucl.ac.uk/id/eprint/18419
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