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Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery

机译:微阵列元分析和跨平台归一化:整合的基因组学可用于可靠的生物标志物发现

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摘要

The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature biomarkers. Microarray platform integration can be conceptually divided into approaches that perform early stage integration (cross-platform normalization) versus late stage data integration (meta-analysis). A growing number of statistical methods and associated software for platform integration are available to the user, however an understanding of their comparative performance and potential pitfalls is critical for best implementation. In this review we provide evidence-based, practical guidance to researchers performing cross-platform integration, particularly with an objective to discover biomarkers.
机译:大量公开可用的微阵列数据的诊断和预后潜力推动了整合来自不同微阵列平台的数据的方法的发展。跨平台整合在适当实施的情况下已被证明可以改善基因签名生物标记物的重现性和健壮性。从概念上讲,微阵列平台集成可以分为执行早期集成(跨平台标准化)与后期数据集成(元分析)的方法。用户可以使用越来越多的用于平台集成的统计方法和相关软件,但是,了解它们的比较性能和潜在的缺陷对于实现最佳效果至关重要。在这篇综述中,我们为进行跨平台整合的研究人员提供基于证据的实用指南,特别是旨在发现生物标记物的目标。

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