NDLI: The sumLINK statistic for genetic linkage analysis in the presence of heterogeneity

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The sumLINK statistic for genetic linkage analysis in the presence of heterogeneity

Content Provider	PubMed Central
Author	Christensen, Gb Knight, S. Camp, Nj
Abstract	We present the “sumLINK” statistic—the sum of multipoint LOD scores for the subset of pedigrees with nominally significant linkage evidence at a given locus—as an alternative to common methods to identify susceptibility loci in the presence of heterogeneity. We also suggest the “sumLOD” statistic (the sum of positive multipoint LOD scores) as a companion to the sumLINK. SumLINK analysis identifies genetic regions of extreme consistency across pedigrees without regard to negative evidence from unlinked or uninformative pedigrees. Significance is determined by an innovative permutation procedure based on genome shuffling that randomizes linkage information across pedigrees. This procedure for generating the empirical null distribution may be useful for other linkage-based statistics as well. Using 500 genome-wide analyses of simulated null data, we show that the genome shuffling procedure results in the correct type 1 error rates for both the sumLINK and sumLOD. The power of the statistics was tested using 100 sets of simulated genome-wide data from the alternative hypothesis from GAW13. Finally, we illustrate the statistics in an analysis of 190 aggressive prostate cancer pedigrees from the International Consortium for Prostate Cancer Genetics, where we identified a new susceptibility locus. We propose that the sumLINK and sumLOD are ideal for collaborative projects and meta-analyses, as they do not require any sharing of identifiable data between contributing institutions. Further, loci identified with the sumLINK have good potential for gene localization via statistical recombinant mapping, as, by definition, several linked pedigrees contribute to each peak.
Related Links	http://dx.doi.org/10.1002/gepi.20414
Ending Page	636
Page Count	9
Starting Page	628
File Format	PDF
ISSN	07410395
e-ISSN	10982272
Journal	Genetic epidemiology
Issue Number	7
Volume Number	33
Language	English
Publisher Date	2009-11-01
Access Restriction	Open
Subject Keyword	Genetics(clinical) Epidemiology Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Epidemiology Genetics (clinical)

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