Linghu Bolan, Franzosa Eric A, Xia Yu
Translational Sciences Department, Novartis Institutes for BioMedical Research, Cambridge, MA, USA.
Methods Mol Biol. 2013;939:215-32. doi: 10.1007/978-1-62703-107-3_14.
Networks of functional associations between genes have recently been successfully used for gene function and disease-related research. A typical approach for constructing such functional linkage gene networks (FLNs) is based on the integration of diverse high-throughput functional genomics datasets. Data integration is a nontrivial task due to the heterogeneous nature of the different data sources and their variable accuracy and completeness. The presence of correlations between data sources also adds another layer of complexity to the integration process. In this chapter we discuss an approach for constructing a human FLN from data integration and a subsequent application of the FLN to novel disease gene discovery. Similar approaches can be applied to nonhuman species and other discovery tasks.
基因之间的功能关联网络最近已成功应用于基因功能和疾病相关研究。构建此类功能连锁基因网络(FLN)的一种典型方法是基于整合各种高通量功能基因组学数据集。由于不同数据源的异构性质及其可变的准确性和完整性,数据整合是一项复杂的任务。数据源之间相关性的存在也给整合过程增加了另一层复杂性。在本章中,我们讨论了一种通过数据整合构建人类FLN的方法,以及该FLN在新型疾病基因发现中的后续应用。类似的方法可以应用于非人类物种和其他发现任务。