grant
Incorporating geography into statistical methods for analysis of population genomic DNA
Organization UNIVERSITY OF MICHIGAN AT ANN ARBORLocation ANN ARBOR, UNITED STATESPosted 1 Jul 2020Deadline 31 Dec 2030
NIHUS FederalResearch GrantFY2026AddressBiologyCausalityClinical geneticsDNA RecombinationDataData SetDiseaseDisorderEnvironmentEtiologyFailureGWA studyGWASGene variantGeneticGenetic DiversityGenetic Population StudyGenetic RecombinationGenetic VariationGenomeGenomic DNAGenomic SegmentGenomicsGenotypeGeographic AreaGeographic LocationsGeographic RegionGeographical LocationGeographyGoalsGraphHistorical DemographyHistoryHumanHuman GeneticsIndividualInvestigatorsLearningLinkMedical GeneticsMethodsModelingModern ManModernizationMovementOrganismPatternPhenotypePopulationPopulation AnalysisPopulation GeneticsPrevalenceRecombinationRecording of previous eventsResearchResearch PersonnelResearchersRoleSamplingShapesSightStatistical MethodsStructureTimeVisionWorkallelic variantbody movementcausationdensitydisease causationdisease riskdisorder riskflexibilityflexiblegDNAgenetic variantgenome segmentgenome wide associationgenome wide association scangenome wide association studygenomewide association scangenomewide association studygenomic datagenomic datasetgenomic regiongenomic variantgeographic sitehistorieshuman diseasehuman genomicsimprovedinsightliving systemnovelpopulation movementprogramssocial rolestatistic methodstoolvisual functionwhole genome association analysiswhole genome association study
Description preview
Project Summary
In humans, genetic variation is distributed geographically, reflecting the history of human movements across
the continents. Understanding these spatial patterns is crucial for many fields in human population genomics,
including the study of human evolutionary history and linking genotypes and phenotypes. Historically, limitations…
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