Multi-tissue and network models for next-generation EQTL studies
Multi-tissue and network models for next-generation EQTL studies
批准号:
9348668
负责人:
Andrew B Nobel
金额:
$39.53万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-07 至 2019-06-30
关键词:
AddressAreaBiologicalCellsCommunitiesComplexComputer softwareCystic FibrosisDataData SetData SourcesDetectionDevelopmentDiseaseDistalFamilyFutureGenesGeneticGenotypeGenotype-Tissue Expression ProjectGoalsIndividualLinear ModelsLinkage DisequilibriumLog-Linear ModelsMethodologyMethodsModelingNetherlandsPathway AnalysisPilot ProjectsPlayProceduresQuantitative Trait LociRecurrenceRegistriesResearchResearch PersonnelResearch ProposalsSamplingScienceSignal TransductionSocial NetworkStatistical MethodsStatistical ModelsStructureTechnologyTestingTimeTissue ModelTissuesTranscriptTwin Multiple Birthbasecomputerized toolsdesignexperienceflexibilitygenome wide association studyhuman diseasehuman tissuenetwork modelsnext generationperipheral bloodstatisticstheoriestooltranscriptome sequencing
中文摘要
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英文摘要
Project Summary
The long-term objective of this research proposal is to provide a framework, and statistical and computational
tools, to advance the analysis and understanding of expression quantitative trait loci (eQTL) in single and
multi-tissue studies, and to elucidate the genotypic basis of differences between tissues. The proposal is
divided into four Aims: (1) to develop bipartite extensions of statistical tools from the analysis of networks that
can enhance the identification of distal (trans) eQTLs; (2) to develop new statistical methods for fast eQTL
association mapping that provide reliable estimates of effect size; (3) to extend our existing multi-tissue eQTL
procedure into a High-Tissue modeling platform capable of handling existing data sets with 20 to 30 tissues;
and (4) to develop gene-based statistical models for eQTL analysis. Development of the proposed methods will
be driven by recent, large-scale eQTL studies in which the investigators have played key roles. The resulting
computational tools will address current, critical shortcomings in the analysis of these new data sets, and will
have broad utility for the wider eQTL analysis community.
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Multi-tissue and network models for next-generation EQTL studies
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批准号:9156968
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项目类别:
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资助金额:$34.82万
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财政年份:2016
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负责人:Andrew B Nobel
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依托单位:
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依托单位:
Systems approaches to link tissue-specific expression to disease
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批准号:8719180
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资助金额:$42.5万
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依托单位:
Systems approaches to link tissue-specific expression to disease
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依托单位:
FACILITATING GTEx, DISEASE, AND GxE ANALYSES VIA FAST EXPRESSION (e)QTL MAPPING
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