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Statistical Methods for DNA Methylation Data

DNA甲基化数据的统计方法

基本信息

批准号：
8036976
负责人：
Shuang Wang
金额：
$ 7.81万
依托单位：
COLUMBIA UNIVERSITY HEALTH SCIENCES
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-04-01 至 2013-03-31
项目状态：
已结题

项目摘要

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.

本研究的总体目标是开发新的统计方法和软件来研究DNA甲基化谱如何与癌症相关。DNA甲基化是DNA的分子修饰，对正常生物体发育很重要。富含CpG二核苷酸的基因在正常组织中通常不甲基化，但在癌症中经常高甲基化。这通常与基因沉默有关，是肿瘤抑制基因失活的重要机制。研究还表明，甲基化谱在不同器官中产生的癌症之间以及在来自同一器官的不同癌症组织学之间存在差异。例如，在白血病和肺癌的不同亚型中发现了不同的DNA甲基化谱。随着阵列技术的快速发展，具有全基因组水平上的DNA甲基化测量的高通量阵列已经变得广泛可用。非常需要开发新的统计模型来评估高通量平台产生的复杂DNA甲基化数据。本项目的具体目标是：（1）开发新的甲基化比例分布模型，以选择癌症和正常受试者之间的差异甲基化位点;（2）提出一种新的分类方法，利用DNA甲基化谱区分肿瘤亚型;（3）开发计算机软件包，实现具体目标1-2中开发的方法。所提出的方法将应用于肿瘤样本/正常组织样本的现有数据和PI正在合作的正在进行的甲基化研究。我们相信，所提出的方法将显着改善目前和未来的努力，在理解癌症中的DNA甲基化谱的意义。公共卫生相关性：抽象叙述开发一系列新颖而强大的统计方法来研究DNA甲基化谱。所提出的方法将显着改善目前和未来的努力，在理解癌症中的DNA甲基化谱的意义。