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dc.contributor.authorFier, Heide
dc.contributor.authorWon, Sungho
dc.contributor.authorProkopenko, Dmitry
dc.contributor.authorAlChawa, Taofik
dc.contributor.authorLudwig, Kerstin U.
dc.contributor.authorFimmers, Rolf
dc.contributor.authorSilverman, Edwin K.
dc.contributor.authorPagano, Marcello
dc.contributor.authorMangold, Elisabeth
dc.contributor.authorLange, Christoph
dc.date.accessioned2013-04-25T18:12:58Z
dc.date.issued2012
dc.identifier.citationFier, Heide, Sungho Won, Dmitry Prokopenko, Taofik AlChawa, Kerstin U. Ludwig, Rolf Fimmers, Edwin K. Silverman, Marcello Pagano, Elisabeth Mangold, and Christoph Lange. 2012. ‘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. Bioinformatics 28(23): 3027-3033.en_US
dc.identifier.issn1367-4803en_US
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:10587968
dc.description.abstractMotivation: 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. Results: In simulation studies, we assess the power of the clustering approach and compare it with existing methodology. Our simulation results suggest that the clustering approach for rare variants is well powered, even in situations that are ideal for standard methods. The efficiency of our spatial clustering approach is not affected by the presence of rare variants that have opposite effect size directions. An application to a sequencing study for non-syndromic cleft lip with or without cleft palate (NSCL/P) demonstrates its practical relevance. The proposed testing strategy is applied to a genomic region on chromosome 15q13.3 that was implicated in NSCL/P etiology in a previous genome-wide association study, and its results are compared with standard approaches. Availability: Source code and documentation for the implementation in R will be provided online. Currently, the R-implementation only supports genotype data. We currently are working on an extension for VCF files. Contact: heide.fier@googlemail.comen_US
dc.language.isoen_USen_US
dc.publisherOxford University Pressen_US
dc.relation.isversionofdoi:10.1093/bioinformatics/bts568en_US
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3516147/pdf/en_US
dash.licenseLAA
dc.title‘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 palateen_US
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden_US
dc.relation.journalBioinformaticsen_US
dash.depositing.authorSilverman, Edwin K.
dc.date.available2013-04-25T18:12:58Z
dc.identifier.doi10.1093/bioinformatics/bts568*
dash.contributor.affiliatedPagano, Marcello
dash.contributor.affiliatedSilverman, Edwin
dash.contributor.affiliatedLange, Christoph


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