A note on generalized Genome Scan Meta-Analysis statistics.

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 Bioinformatics

journal_title

BMC bioinformatics

authors

Koziol JA,Feng AC

doi

10.1186/1471-2105-6-32

keywords:

subject

Has Abstract

pub_date

2005-02-17 00:00:00

pages

32

issn

1471-2105

pii

1471-2105-6-32

journal_volume

6

pub_type

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