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

项目摘要/摘要 这项应用将研究来自圣犹大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。发病时间和发病时间都收集了，但目前的分析未能分析 由于数据缺失率较高，发病时间较长。DNA样本被收集和测序，但也没有进行分析。 我们提出了在存在缺失数据的情况下通过考虑某些发病来分析疾病发病时间的创新方法 将时间看作区间删失，提出了超高维区间删失结果分析的新方法 遗传协变量。我们将对整体执行基于单个变量的分析和基于罕见变量聚合的分析 基因组测序数据。我们的目标是评估口腔疾病的动态和相关的风险因素，包括环境 因素、遗传因素以及它们之间的相互作用。具体来说，目标是：1)。开发非参数和半参数 具有区间删失结果的超高维数据筛选方法；发展一种受惩罚的回归 目标1的数据降维方法；3)。将目标1和目标2中开发的方法应用于 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。这个 拟议研究的主要目标是利用现有方法和开发新的统计程序来 对全基因组和口腔健康数据进行适当的分析，以更深入地了解基因 牙齿发育和疾病的架构。

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.