Abstract:
BACKGROUND:Wise et al. introduced a rank-based statistical technique for meta-analysis of genome scans, the Genome Scan Meta-Analysis (GSMA) method. Levinson et al. recently described two generalizations of the GSMA statistic: (i) a weighted version of the GSMA statistic, so that different studies could be ascribed different weights for analysis; and (ii) an order statistic approach, reflecting the fact that a GSMA statistic can be computed for each chromosomal region or bin width across the various genome scan studies. RESULTS:We provide an Edgeworth approximation to the null distribution of the weighted GSMA statistic, and, we examine the limiting distribution of the GSMA statistics under the order statistic formulation, and quantify the relevance of the pairwise correlations of the GSMA statistics across different bins on this limiting distribution. We also remark on aggregate criteria and multiple testing for determining significance of GSMA results. CONCLUSION:Theoretical considerations detailed herein can lead to clarification and simplification of testing criteria for generalizations of the GSMA statistic.
journal_name
BMC Bioinformaticsjournal_title
BMC bioinformaticsauthors
Koziol JA,Feng ACdoi
10.1186/1471-2105-6-32keywords:
subject
Has Abstractpub_date
2005-02-17 00:00:00pages
32issn
1471-2105pii
1471-2105-6-32journal_volume
6pub_type
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