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Meta-analysis of SNPs involved in variance heterogeneity using Levene's test for equal variances.


ABSTRACT: Meta-analysis is a commonly used approach to increase the sample size for genome-wide association searches when individual studies are otherwise underpowered. Here, we present a meta-analysis procedure to estimate the heterogeneity of the quantitative trait variance attributable to genetic variants using Levene's test without needing to exchange individual-level data. The meta-analysis of Levene's test offers the opportunity to combine the considerable sample size of a genome-wide meta-analysis to identify the genetic basis of phenotypic variability and to prioritize single-nucleotide polymorphisms (SNPs) for gene-gene and gene-environment interactions. The use of Levene's test has several advantages, including robustness to departure from the normality assumption, freedom from the influence of the main effects of SNPs, and no assumption of an additive genetic model. We conducted a meta-analysis of the log-transformed body mass index of 5892 individuals and identified a variant with a highly suggestive Levene's test P-value of 4.28E-06 near the NEGR1 locus known to be associated with extreme obesity.

SUBMITTER: Deng WQ 

PROVIDER: S-EPMC3925287 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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Meta-analysis of SNPs involved in variance heterogeneity using Levene's test for equal variances.

Deng Wei Q WQ   Asma Senay S   Paré Guillaume G  

European journal of human genetics : EJHG 20130807 3


Meta-analysis is a commonly used approach to increase the sample size for genome-wide association searches when individual studies are otherwise underpowered. Here, we present a meta-analysis procedure to estimate the heterogeneity of the quantitative trait variance attributable to genetic variants using Levene's test without needing to exchange individual-level data. The meta-analysis of Levene's test offers the opportunity to combine the considerable sample size of a genome-wide meta-analysis  ...[more]

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