PinSnps: structural and functional analysis of SNPs in the context of protein interaction networks
PinSnps: structural and functional analysis of SNPs in the context of protein interaction networks
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DOI：
10.1093/bioinformatics/btw153
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发表时间：
2016-08-15
期刊：
影响因子：
5.8
通讯作者：
Fraternali, Franca
中科院分区：
文献类型：
--
作者：
Lu, Hui-Chun;Braga, Julian Herrera;Fraternali, Franca
我们提出了一个实用的计算管道，通过使用映射到蛋白质结构上的遗传和功能信息来容易地执行蛋白质-蛋白质相互作用网络的数据分析。我们提供了所选遗传变异和/或SNP的可用蛋白质结构及其区域(表面、界面、核心和无序)的3D表示，并预测了通过一系列方法测量的变异对蛋白质的影响。我们总共定位了来自OMIM的2587个与遗传疾病相关的SNPs，来自COSMIC的587873个与癌症相关的变体，以及来自DBSNP的1484 045个SNPs。所有结果数据都可以由用户与R-脚本一起下载，以计算选定结构区域中SNP/变体的丰度。
We present a practical computational pipeline to readily perform data analyses of protein- protein interaction networks by using genetic and functional information mapped onto protein structures. We provide a 3D representation of the available protein structure and its regions (surface, interface, core and disordered) for the selected genetic variants and/or SNPs, and a prediction of the mutants' impact on the protein as measured by a range of methods. We have mapped in total 2587 genetic disorder-related SNPs from OMIM, 587 873 cancer-related variants from COSMIC, and 1 484 045 SNPs from dbSNP. All result data can be downloaded by the user together with an R-script to compute the enrichment of SNPs/variants in selected structural regions.