000145644 001__ 145644
000145644 005__ 20200925192554.0
000145644 037__ $$aDZNE-2020-00974
000145644 041__ $$aEnglish
000145644 082__ $$a610
000145644 1001_ $$0P:(DE-HGF)0$$aProkopenko, D.$$b0
000145644 1112_ $$a43rd European Mathematical Genetics Meeting 2015$$cBrest$$d2015-04-16 - 2015-04-17$$gEMGM$$wFrance
000145644 245__ $$aA36: Utilizing the Jaccard Index to Reveal PopulationStratification in Sequencing Data: A SimulationStudy and an Application to the 1000 GenomesProject
000145644 260__ $$c2015
000145644 3367_ $$0PUB:(DE-HGF)1$$2PUB:(DE-HGF)$$aAbstract$$babstract$$mabstract$$s1597407370_15935
000145644 3367_ $$033$$2EndNote$$aConference Paper
000145644 3367_ $$2BibTeX$$aINPROCEEDINGS
000145644 3367_ $$2DRIVER$$aconferenceObject
000145644 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$mjournal
000145644 3367_ $$2DataCite$$aOutput Types/Conference Abstract
000145644 3367_ $$2ORCID$$aOTHER
000145644 520__ $$aPopulation stratification is one of the major sources of confounding in genetic association studies, potentially causing falsepositive and false-negative results. The effectiveness of existingadjustment approaches which are mostly built on the estimationof the genetic variance/covariance matrix is unclear for rare variants, since those variants are genetically much ‘younger’ andmight represent a different pattern of population structure.Here, we present a novel approach for the identification of population substructure in high density-genotyping data/next generation sequencing data. The approach exploits the co-appearances of rare genetic variants in individuals. The method can beapplied to all available genetic loci, does not require linkage disequilibrium (LD) pruning, and is computationally fast. Usingsequencing data from the 1000 Genomes Project, the features of the approach are illustrated and compared to existing methodology (i.e. EIGENSTRAT). We find that our approach works particularly well for genetic loci with very small minor allele frequencies. The results suggest that the inclusion of rare-variantdata/sequencing data in our approach provides a much higherresolution-picture of population-substructure than it can be obtained with existing methodology. Furthermore, we performedextensive simulation studies based on the minor allele frequencies of the European populations. We find scenarios where ourmethod was able to control the type 1 error more precisely andshowed higher power.
000145644 536__ $$0G:(DE-HGF)POF3-345$$a345 - Population Studies and Genetics (POF3-345)$$cPOF3-345$$fPOF III$$x0
000145644 7001_ $$0P:(DE-HGF)0$$aHecker, J.$$b1
000145644 7001_ $$0P:(DE-HGF)0$$aSilverman, E.$$b2
000145644 7001_ $$0P:(DE-HGF)0$$aPagano, M.$$b3
000145644 7001_ $$0P:(DE-HGF)0$$aNoethen, M.$$b4
000145644 7001_ $$0P:(DE-2719)9000181$$aLange, Christoph$$b5$$udzne
000145644 7001_ $$0P:(DE-HGF)0$$aLoehlein Fie, H.$$b6
000145644 773__ $$0PERI:(DE-600)1482710-4$$n1$$p44$$tHuman heredity$$v79$$x0001-5652$$y2015
000145644 8564_ $$uhttps://www.karger.com/Article/PDF/381109
000145644 909CO $$ooai:pub.dzne.de:145644$$pVDB
000145644 9101_ $$0I:(DE-588)1065079516$$6P:(DE-2719)9000181$$aDeutsches Zentrum für Neurodegenerative Erkrankungen$$b5$$kDZNE
000145644 9131_ $$0G:(DE-HGF)POF3-345$$1G:(DE-HGF)POF3-340$$2G:(DE-HGF)POF3-300$$aDE-HGF$$bForschungsbereich Gesundheit$$lErkrankungen des Nervensystems$$vPopulation Studies and Genetics$$x0
000145644 9141_ $$y2015
000145644 915__ $$0StatID:(DE-HGF)0410$$2StatID$$aAllianz-Lizenz$$d2020-01-11$$wger
000145644 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz$$d2020-01-11$$wger
000145644 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bHUM HERED : 2018$$d2020-01-11
000145644 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2020-01-11
000145644 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2020-01-11
000145644 915__ $$0StatID:(DE-HGF)0310$$2StatID$$aDBCoverage$$bNCBI Molecular Biology Database$$d2020-01-11
000145644 915__ $$0StatID:(DE-HGF)0320$$2StatID$$aDBCoverage$$bPubMed Central$$d2020-01-11
000145644 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2020-01-11
000145644 915__ $$0StatID:(DE-HGF)0110$$2StatID$$aWoS$$bScience Citation Index$$d2020-01-11
000145644 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2020-01-11
000145644 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2020-01-11
000145644 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2020-01-11
000145644 915__ $$0StatID:(DE-HGF)1190$$2StatID$$aDBCoverage$$bBiological Abstracts$$d2020-01-11
000145644 915__ $$0StatID:(DE-HGF)1030$$2StatID$$aDBCoverage$$bCurrent Contents - Life Sciences$$d2020-01-11
000145644 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2020-01-11
000145644 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2020-01-11
000145644 9201_ $$0I:(DE-2719)7000008$$kU T4 Researchers - Bonn$$lU T4 Researchers - Bonn$$x0
000145644 980__ $$aabstract
000145644 980__ $$aVDB
000145644 980__ $$ajournal
000145644 980__ $$aI:(DE-2719)7000008
000145644 980__ $$aUNRESTRICTED