Statistical Methods for DNA Methylation Data
Statistical Methods for DNA Methylation Data
批准号:
8036976
负责人:
Shuang Wang
金额:
$7.81万
依托单位国家:
美国
项目类别:
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-04-01 至 2013-03-31
关键词:
Air PollutantsAromatic Polycyclic HydrocarbonsCancer HistologyChildClassificationComplexComputer softwareCpG dinucleotideCytosineDNADNA MethylationDNA Modification ProcessDataData SetDevelopmentEnvironmental HealthFutureGene SilencingGenesGenomicsHead and Neck NeoplasmsMalignant NeoplasmsMalignant neoplasm of lungMeasuresMethodsMethylationModelingMolecularNormal tissue morphologyOrganOrganismPilot ProjectsPositioning AttributeProcessSamplingSeriesStatistical MethodsStatistical ModelsTissue SampleTumor SubtypeTumor-Suppressor Gene InactivationUniversitiesabstractingcohortgenome-widehigh throughput technologyimprovedleukemiamethyl groupnovelperformance testsprenatalpublic health relevancesimulationsoftware developmenttumoruser-friendly
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): Statistical Methods for DNA Methylation Data Abstract The overall objective of this study is to develop novel statistical methods and software to study how DNA methylation profiles associated with cancers. DNA methylation is a molecular modification of DNA that is important for normal organism development. Genes that are rich in CpG dinucleotides are usually not methylated in normal tissues, but are frequently hypermethylated in cancer. This is often associated with gene silencing and is an important mechanism for the inactivation of tumor suppressor genes. Studies have also suggested that methylation profiles differ between cancers arising in different organs and between different cancer histologies from the same organ. For example, different DNA methylation profiles are found in different subtypes of leukemia and lung cancer. With the rapid development in array technologies, high-throughput arrays with DNA mathylation measures on the genome-wide level have become widely available. There is a great need for development of novel statistical models to evaluate complex DNA methylation data generated with high-throughput platforms. The specific objectives of this project are: (1) to develop novel models for the distribution of methylation proportions to select differentially methylated loci between cancer and normal subjects; (2) to propose a new classification method that differentiates tumor subtypes using DNA methylation profiles; (3) to develop computer software packages that implement methods developed in specific aims 1-2. The proposed methods will be applied to an existing data with tumor samples/normal tissue samples and an ongoing methylation study the PI is collaborating. We believe the proposed methods will significantly improve current and future efforts in understanding the significance of DNA methylation profiles in cancers.
PUBLIC HEALTH RELEVANCE: Abstract narrative To develop a series of novel and powerful statistical methods to study DNA methylation profiles. The proposed methods will significantly improve current and future efforts in understanding the significance of DNA methylation profiles in cancers.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
DOI:
10.1002/gepi.20619
发表时间:
2011-11
期刊:
GENETIC EPIDEMIOLOGY
影响因子:
2.1
作者:
[Wang, Shuang]
通讯作者:
Wang, Shuang
Hepatic stellate cell plasticity and maladaptive fibrogenic memory in chronic liver disease
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批准号:10638234
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项目类别:
-
资助金额:$59.22万
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财政年份:2023
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负责人:Shuang Wang
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依托单位:
Protecting the pRivacy Of Genomes in Research StudieS (PROGRESS)
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批准号:8804836
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项目类别:
-
资助金额:$8.99万
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财政年份:2014
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负责人:Shuang Wang
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依托单位:
Statistical Methods for DNA Methylation Data
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批准号:7898457
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项目类别:
-
资助金额:$8.04万
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财政年份:2010
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负责人:Shuang Wang
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依托单位:
海外基金