Innovative Statistical Analysis for Genome-Wide Data with General Interval-Censored Outcomes of Oral Health in Childhood Cancer Survivors

对全基因组数据的创新统计分析以及儿童癌症幸存者口腔健康的一般区间审查结果

基本信息

批准号：
10532639
负责人：
Yimei Li
金额：
$ 16.23万
依托单位：
UNIVERSITY OF TX MD ANDERSON CAN CTR
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-12-01 至 2024-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10532639
关键词：
Innovative Statistical Analysis Genome Wide

项目摘要

Project Summary/Abstract This application will study the oral sequelae in childhood cancer survivors from the St. Jude Life cohort and Childhood Cancer Survivor Study cohort. Both disease onset and onset time were collected, but current analyses fail to analyze the disease onset time due to high rate of missing data. DNA samples were collected and sequenced but not analyzed either. We propose innovative ways to analyze the disease onset time in the presence of missing data by considering some onset time as interval-censored, and propose new methods for analyzing interval-censored outcomes with ultrahigh-dimensional genetic covariates. We will perform both single variant-based and rare variant aggregation-based analysis for the whole genome sequencing data. We aim to estimate oral disease dynamics and associated risk factors including environmental factors, genetic factors, and their interaction. Specifically, the aims are: 1). Develop nonparametric and semiparametric screening methods for ultrahigh-dimensional data with interval-censored outcomes; 2). Develop a penalized regression method for data with reduced dimensionality from Aim 1; 3). Apply the methods developed in Aim 1 and Aim 2 to the SJLIFE and CCSS data. We will develop and share multiple user-friendly R codes associated with the new methods. The main objective of the proposed research is to employ the existing methods and develop new statistical procedures to perform appropriate analysis on the whole-genome and oral health data for a deeper understanding of the genetic architecture of tooth development and disease.

项目摘要/摘要该应用将研究来自圣裘德生活队列和童年的儿童癌症幸存者的口腔后遗症癌症幸存者研究队列。疾病发作和发作时间都收集了，但是当前的分析未能分析疾病的发作时间由于缺失的数据率很高。收集并测序DNA样品，但也没有分析。我们提出了创新的方法来分析疾病发作时间在缺失数据的情况下通过考虑某些发作作为间隔审查的时间，并提出了分析超高维的间隔审查结果的新方法遗传协变量。我们将对整体进行基于单个变体和稀有变体聚合分析基因组测序数据。我们旨在估计口腔疾病动态和相关风险因素，包括环境因素，遗传因素及其相互作用。具体而言，目的是：1）。开发非参数和半摩托车具有间隔审查结果的超高维数据的筛选方法； 2）。发展惩罚回归 AIM 1降低维度的数据的方法； 3）。应用AIM 1中开发的方法，AIM 2与 SJLIFE和CCSS数据。我们将开发和共享与新方法相关的多个用户友好的R码。这拟议研究的主要目的是采用现有方法并制定新的统计程序对整个基因组和口服健康数据进行适当的分析，以更深入地了解遗传牙齿发育和疾病的建筑。