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‘Location, Location, Location’: a spatial approach for rare variant analysis and an application to a study on non-syndromic cleft lip with or without cleft palate
Author(s) -
Heide Fier,
Sungho Won,
Dmitry Prokopenko,
Taofik AlChawa,
Kerstin U. Ludwig,
Rolf Fimmers,
Edwin K. Silverman,
Michele Pagano,
Elisabeth Mangold,
Christoph Lange
Publication year - 2012
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bts568
Subject(s) - cluster analysis , computer science , computational biology , statistic , chromosome , curse of dimensionality , data mining , biology , artificial intelligence , genetics , mathematics , statistics , gene
For the analysis of rare variants in sequence data, numerous approaches have been suggested. Fixed and flexible threshold approaches collapse the rare variant information of a genomic region into a test statistic with reduced dimensionality. Alternatively, the rare variant information can be combined in statistical frameworks that are based on suitable regression models, machine learning, etc. Although the existing approaches provide powerful tests that can incorporate information on allele frequencies and prior biological knowledge, differences in the spatial clustering of rare variants between cases and controls cannot be incorporated. Based on the assumption that deleterious variants and protective variants cluster or occur in different parts of the genomic region of interest, we propose a testing strategy for rare variants that builds on spatial cluster methodology and that guides the identification of the biological relevant segments of the region. Our approach does not require any assumption about the directions of the genetic effects.

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