Association study based on topological constraints of protein–protein interaction networks

Association study based on topological constraints of protein–protein interaction networks
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基于蛋白质-蛋白质相互作用网络拓扑约束的关联研究

DOI:
10.1038/s41598-020-67875-w
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发表时间:
2020
期刊:
影响因子:
4.6
通讯作者:
Qin, Hong
Qin, Hong
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Guo, Hao-Bo;Qin, Hong

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蛋白质-蛋白质相互作用网络(PIN)的非随机相互作用模式具有丰富的生物学信息,但其潜力尚未在组学研究中得到充分利用。在这里,我们提出了一种基于网络排列的关联研究(NetPAS)方法,该方法基于排列零模型和经验网络之间的比较来衡量两组基因之间观察到的相互作用。这使得NetPAS能够在网络拓扑的约束下评估与不同表型相关的基因集之间的关系。我们展示了NetPAS在50个精心策划的基因集中的效用,并使用Z分数、修改的Z分数、p值和Jaccard指数对关联研究进行了比较。使用NetPAS,从OMIM的19个基因集的关联评分生成加权人类疾病网络。我们还将NetPAS应用于来自基因本体和通路注释的基因集,结果表明NetPAS发现了DAVID和WebGestalt遗漏的功能术语。总的来说,我们表明NetPAS可以考虑分子网络的拓扑约束,并提供比现有方法新的视角。
The non-random interaction pattern of a protein–protein interaction network (PIN) is biologically informative, but its potentials have not been fully utilized in omics studies. Here, we propose a network-permutation-based association study (NetPAS) method that gauges the observed interactions between two sets of genes based on the comparison between permutation null models and the empirical networks. This enables NetPAS to evaluate relationships, constrained by network topology, between gene sets related to different phenotypes. We demonstrated the utility of NetPAS in 50 well-curated gene sets and comparison of association studies using Z-scores, modified Zʹ-scores, p-values and Jaccard indices. Using NetPAS, a weighted human disease network was generated from the association scores of 19 gene sets from OMIM. We also applied NetPAS in gene sets derived from gene ontology and pathway annotations and showed that NetPAS uncovered functional terms missed by DAVID and WebGestalt. Overall, we show that NetPAS can take topological constraints of molecular networks into account and offer new perspectives than existing methods.
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