Statistical Methods for Analyzing Birth Defects Cohorts
Statistical Methods for Analyzing Birth Defects Cohorts
批准号:
10372041
负责人:
HONGYU ZHAO
金额:
$16.75万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-04-01 至 2025-03-31
关键词:
AddressAffectBiologicalBiotechnologyChildCommunitiesComputer softwareCongenital AbnormalityDataData AggregationData SetDefectDiseaseDisease modelEconomic BurdenEtiologyFamilyFundingFutureGenesGeneticGenetic studyGenomeGenomicsGoalsGuidelinesHeterogeneityHeterozygoteImmune System DiseasesIndividualInheritedJointsMalignant Childhood NeoplasmMental disordersMetabolicMethodsMutationNewborn InfantParentsPathway interactionsPediatric ResearchPerformancePhenotypePlayResearchResearch PersonnelRoleSample SizeSignal TransductionSocietiesStatistical MethodsStructural Congenital AnomaliesTechnologyUnited States National Institutes of HealthVariantWorkcohortcongenital heart disorderdata resourcede novo mutationdisorder riskexome sequencingfamily burdengene discoverygenomic datahealth economicsimprovednext generation sequencingnovelphenotypic datapleiotropismprogramsrisk predictionsoftware developmentsuccesstool
中文摘要
点击翻译按钮获取中文摘要
英文摘要
Project Summary
Birth defects cause significant health and economic burdens to families and societies globally. In recent years,
advances in biotechnologies, such as next-generation sequencing, have helped to identify many disease-
causing genes for birth defects and childhood cancers. Although the identified genes only explain a small
proportion of the cases, these advancements demonstrate the promise of identifying more birth defect-causing
genes from the analysis of sequencing data through powerful statistical methods. The NIH Common Fund
established the Gabriella Miller Kids First Pediatric Research Program (Kids First) to “develop a pediatric
research data resource populated by genome sequence and phenotype data that will be of high value for the
communities of investigators who study the genetics of childhood cancers and/or structural birth defects.” The
ultimate goal of this project is to develop, implement, and apply novel statistical methods to improve the power
of identifying genes causing birth defects across a number of conditions using data from the Kids First Data
Resource Center and to make the developed tools available to the scientific community. This will be
accomplished through three specific aims. First, we will develop a statistical framework that can simultaneously
consider different disease models – including both de novo mutations and rare inherited variants – to more
effectively identify disease-causing genes from whole exome sequencing data. Second, we will develop
statistical methods to quantify the degree of shared de novo mutation contributions to different birth defects
and also methods that can leverage this shared genetics to identify disease-causing genes. Third, after
evaluating the performance of our developed methods, we will implement these methods and apply them to the
birth defect cohorts currently available at the Kids First Data Resource Center as well as other data sets that
will be added in the future. We will also disseminate the software to the scientific community. In accomplishing
our aims, we will contribute new statistical tools to analyze birth defects cohorts as well as make new biological
discoveries of genes and pathways for different birth defects.
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科研奖励(0)
会议论文
Statistical Methods for Genetic Risk Predictions across Diverse Populations
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批准号:10662188
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项目类别:
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资助金额:$56.87万
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财政年份:2022
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负责人:HONGYU ZHAO
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依托单位:
Statistical Methods for Genetic Risk Predictions across Diverse Populations
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批准号:10391800
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项目类别:
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资助金额:$57.92万
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财政年份:2022
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负责人:HONGYU ZHAO
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依托单位:
Data Management Core
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批准号:10698039
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项目类别:
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资助金额:$24.66万
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财政年份:2022
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负责人:HONGYU ZHAO
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依托单位:
Statistical Methods for Genetic Risk Predictions across Diverse Populations
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批准号:10731582
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资助金额:$8.39万
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财政年份:2022
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负责人:HONGYU ZHAO
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依托单位:
Analytical Core
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批准号:9336550
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项目类别:
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资助金额:$9.61万
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财政年份:2011
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负责人:HONGYU ZHAO
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依托单位:
Analytical Core
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批准号:8555273
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项目类别:
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资助金额:$14.5万
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财政年份:2011
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负责人:HONGYU ZHAO
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依托单位:
Lost-of-function variants in the 1000 genomes data set and implications to GWAS
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批准号:7882977
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项目类别:
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资助金额:$26.2万
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财政年份:2010
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负责人:HONGYU ZHAO
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依托单位:
Lost-of-function variants in the 1000 genomes data set and implications to GWAS
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批准号:8141451
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项目类别:
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资助金额:$27.07万
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财政年份:2010
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负责人:HONGYU ZHAO
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依托单位:
International Symposium on Genome-Wide Association Studies
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批准号:7193776
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项目类别:
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资助金额:$3.75万
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财政年份:2006
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负责人:HONGYU ZHAO
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依托单位:
Theoretical Studies of Linkage Disequilibrium
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批准号:6879911
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项目类别:
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资助金额:$9.94万
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财政年份:2004
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负责人:HONGYU ZHAO
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依托单位:
Statistical Methods to Map Genes for Complex Traits
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批准号:6789446
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项目类别:
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资助金额:$23.29万
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财政年份:1999
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负责人:HONGYU ZHAO
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依托单位:
STATISTICAL METHODS TO MAP GENES FOR COMPLEX TRAITS
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批准号:2866661
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项目类别:
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资助金额:$14.77万
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财政年份:1999
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负责人:HONGYU ZHAO
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依托单位:
Statistical Methods to Map Genes for Complex Traits
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批准号:7032625
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项目类别:
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资助金额:$30.68万
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财政年份:1999
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负责人:HONGYU ZHAO
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依托单位:
STATISTICAL METHODS FOR NONDISJUNCTION DATA
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批准号:6387992
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项目类别:
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资助金额:$10.09万
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财政年份:1999
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负责人:HONGYU ZHAO
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依托单位:
Statistical Methods to Map Genes for Complex Traits
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批准号:7809719
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项目类别:
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资助金额:$35.17万
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财政年份:1999
-
负责人:HONGYU ZHAO
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依托单位:
STATISTICAL METHODS TO MAP GENES FOR COMPLEX TRAITS
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批准号:6351311
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项目类别:
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资助金额:$21.3万
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财政年份:1999
-
负责人:HONGYU ZHAO
-
依托单位:
Statistical Methods to Map Genes for Complex Traits
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批准号:6608838
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项目类别:
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资助金额:$23.03万
-
财政年份:1999
-
负责人:HONGYU ZHAO
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依托单位:
Statistical Methods to Map Genes for Complex Traits
-
批准号:8231513
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项目类别:
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资助金额:$34.82万
-
财政年份:1999
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负责人:HONGYU ZHAO
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依托单位:
Statistical Methods to Map Genes for Complex Traits
-
批准号:6542951
-
项目类别:
-
资助金额:$22.82万
-
财政年份:1999
-
负责人:HONGYU ZHAO
-
依托单位:
Statistical Methods to Map Genes for Complex Traits
-
批准号:8434142
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项目类别:
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资助金额:$33.6万
-
财政年份:1999
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负责人:HONGYU ZHAO
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依托单位:
海外基金