Integrating heterogeneous genomic data to accurately identify disease subtypes.
Integrating heterogeneous genomic data to accurately identify disease subtypes.
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整合异质基因组数据以准确识别疾病亚型
DOI：
10.1186/s12920-015-0154-5
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发表时间：
2015-11-20
影响因子：
2.7
通讯作者：
Jin Q
中科院分区：
文献类型：
--
作者：
Ren X;Fu H;Jin Q
背景高通量生物技术已被广泛用于从表观基因组学、基因组学和转录组学等各个角度表征临床样本。然而，由于这些技术及其输出的异质性，对各种类型数据的单独分析很难创建疾病亚型的全面视图。综合方法是迫切需要的。方法在本研究中，我们评估了阻碍异构疾病数据类型综合分析的可能问题，并提出了iBFE，一种有效且高效的计算方法，从特征提取的角度颠覆这些问题。结果在模拟和真实数据集上的严格实验表明，iBFE可以轻松克服因尺度冲突、噪声冲突、患者关系不完整以及患者关系之间冲突引起的问题，并且iBFE可以有效结合DNA甲基化、 mRNA表达和microRNA（miRNA）表达数据集可准确识别预后显着不同的疾病亚型。结论siBFE是一种有效且高效的异质基因组数据综合分析方法，可准确识别疾病亚型。 iBFE 的 Matlab 代码可以从 http://zhangroup.aporc.org/iBFE 免费获取。
BackgroundHigh-throughput biotechnologies have been widely used to characterize clinical samples from various perspectives e.g., epigenomics, genomics and transcriptomics. However, because of the heterogeneity of these technologies and their outputs, individual analysis of the various types of data is hard to create a comprehensive view of disease subtypes. Integrative methods are of pressing need.MethodsIn this study, we evaluated the possible issues that hamper integrative analysis of the heterogeneous disease data types, and proposed iBFE, an effective and efficient computational method to subvert those issues from a feature extraction perspective.ResultsStrict experiments on both simulated and real datasets demonstrated that iBFE can easily overcome issues caused by scale conflicts, noise conflicts, incompleteness of patient relationships, and conflicts between patient relationships, and that iBFE can effectively combine the merits of DNA methylation, mRNA expression and microRNA (miRNA) expression datasets to accurately identify disease subtypes of significantly different prognosis.ConclusionsiBFE is an effective and efficient method for integrative analysis of heterogeneous genomic data to accurately identify disease subtypes. The Matlab code of iBFE is freely available from http://zhangroup.aporc.org/iBFE .
用于揭示和预测癌症的微妙亚型的统一计算模型
影响因子：
3
作者：
Ren X;Wang Y;Wang J;Zhang XS
通讯作者：
Zhang XS