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A simple method for assessing the strength of evidence for association at the level of the whole gene

Authors Curtis D, Vine AE, Knight J

Published 17 November 2008 Volume 2008:1 Pages 115—120


Review by Single-blind

Peer reviewer comments 5

David Curtis1, Anna E Vine1, Jo Knight2

1Centre for Psychiatry, Queen Mary’s School of Medicine and Dentistry, London E1 1BB, UK; 2Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, De Crespigny Park, London SE5 8AF, UK

Introduction: It is expected that different markers may show different patterns of association with different pathogenic variants within a given gene. It would be helpful to combine the evidence implicating association at the level of the whole gene rather than just for individual markers or haplotypes. Doing this is complicated by the fact that different markers do not represent independent sources of information.

Method: We propose combining the p values from all single locus and/or multilocus analyses of different markers according to the formula of Fisher, X = Σ(−2ln(pi)), and then assessing the empirical significance of this statistic using permutation testing. We present an example application to 19 markers around the HTRA2 gene in a case-control study of Parkinson’s disease.

Results: Applying our approach shows that, although some individual tests produce low p values, overall association at the level of the gene is not supported.

Discussion: Approaches such as this should be more widely used in assimilating the overall evidence supporting involvement of a gene in a particular disease. Information can be combined from biallelic and multiallelic markers and from single markers along with multimarker analyses. Single genes can be tested or results from groups of genes involved in the same pathway could be combined in order to test biologically relevant hypotheses. The approach has been implemented in a computer program called COMBASSOC which is made available for downloading.

Keywords: Fisher, significance, genetic marker

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