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Methodological study demonstrates robust permutation tests for allelic associations in case-control datasets, enabling memory-efficient multi-marker analysis.
In this short report, we address some practical problems in performing likelihood-based allelic association analysis of case-control data. Model-free statistics are proposed and their properties assessed by simulation, and procedures based on permutation tests are described for marker-marker as well as marker-disease associations. A memory-efficient algorithm is developed which enables several highly polymorphic markers to be analysed.
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Zhao et al. (1999) studied this question.
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