Statistical Methods for Analysis of Array CGH Data

本提案的主要目标是在“信号处理”的个体水平和检测模式的群体水平上为阵列比较基因组杂交（aCGH）数据开发计算易于处理的统计分析方法。在个体分析层面，我们的目标是通过同时分析多染色体和杂交来改进目前可用的方法，这些方法利用了共同的特征，同时考虑了染色体内部和染色体之间以及杂交之间的可变性。在人群水平上，我们将开发新的方法来定位基因组不稳定的共同区域，并使用临床终点（如生存率）对患者进行聚类。这些方法是由神经胶质瘤研究和脑膜瘤研究的aCGH数据集驱动的，并将应用于这些数据集。相关性：恶性胶质瘤是人类最常见的原发性脑肿瘤。然而，它们的病理分类问题使患者管理复杂化，并引发了对分子诊断方法的相当大的兴趣。我们的团队目前正在开发aCGH的方法，我们假设，可以提供一种敏感，特异性，成本效益和快速的方法来评估人类恶性胶质瘤的相关遗传变化。脑膜瘤是一种常见的颅内肿瘤，常见于2型神经纤维瘤病（NF2）患者，也偶尔发生在没有种系NF2突变的个体中。有必要寻找可能在这些散发性脑膜瘤的发生和发展中起作用的遗传机制。此外，aCGH分析可能有助于家族性多发性脑膜瘤的鉴别诊断。阵列CGH有望揭示肿瘤中小的不平衡染色体事件，并可以提供关于不平衡染色体片段（ICS）边界的特定信息。要对这些重要数据进行有效和有效的分析，需要健全的统计方法。

The primary goal of this proposal is to develop computationally tractable methods of statistical analysis for array comparative genomic hybridization (aCGH) data at both the individual level of "signal processing" and the population level of detecting patterns. At the individual level of analysis, we aim to improve upon currently available methods through a simultaneous analysis of multiple chromosomes and hybridizations that exploits features that are shared in common, while accounting for variability within and between chromosomes and between hybridizations. At the population-level, we will develop novel methods for locating common regions of genomic instability and for clustering patients using clinical endpoints, such as survival. These methods are motivated by, and will be applied to, aCGH data sets from glioma studies and meningioma studies. Relevance: Malignant gliomas are the most common primary human brain tumors. Problems in their pathological classification, however, complicate patient management and have sparked considerable interest in molecular diagnostic approaches. Our group is currently developing methods for aCGH that, we hypothesize, can provide a sensitive, specific, cost-effective and rapid method to assess human malignant gliomas for relevant genetic changes. Meningioma, a common intracranial tumor found frequently in patients with neurofibromatosis type 2 (NF2), also occurs sporadically in individuals without germline NF2 mutations. It is necessary to seek genetic mechanisms that may operate in the initiation and progression of these sporadic meningiomas. In addition, aCGH profiling will likely be useful for differential diagnosis of familial multiple meningioma. Array CGH holds promise for uncovering small imbalanced chromosomal events in tumors and can provide specific information about the boundaries of the imbalanced chromosome segments (ICS). Sound statistical methods are required for efficient and valid analyses of these important data.