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

Abstract

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 = ∑(−2ln(p_i)), 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

Acknowledgments

AEV was supported by Wellcome Trust Project Grant, Grant No. 076392. JK was supported by an MRC Bioinformatics Training Fellowship, Grant No. G0501329.

Disclosures

The authors disclose no conflicts of interest.