PINBPA：用于全基因组关联研究（GWAS）数据网络分析的Cytoscape应用程序。

PINBPA: cytoscape app for network analysis of GWAS data.

作者信息

Wang Lili, Matsushita Takuya, Madireddy Lohith, Mousavi Parvin, Baranzini Sergio E

机构信息

School of Computing, Queen's University, 25 Union Street, Goodwin Hall, Kingston, Ontario K7L 3N6, Canada and Department of Neurology, University of California San Francisco, 675 Nelson Rising Lane, Room 215, San Francisco, CA 94158, USA.

出版信息

Bioinformatics. 2015 Jan 15;31(2):262-4. doi: 10.1093/bioinformatics/btu644. Epub 2014 Sep 25.

DOI:10.1093/bioinformatics/btu644

PMID:25260698

Abstract

UNLABELLED

Protein interaction network-based pathway analysis (PINBPA) for genome-wide association studies (GWAS) has been developed as a Cytoscape app, to enable analysis of GWAS data in a network fashion. Users can easily import GWAS summary-level data, draw Manhattan plots, define blocks, prioritize genes with random walk with restart, detect enriched subnetworks and test the significance of subnetworks via a user-friendly interface.

AVAILABILITY AND IMPLEMENTATION

PINBPA app is freely available in Cytoscape app store.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

未标注

基于蛋白质相互作用网络的全基因组关联研究（GWAS）通路分析（PINBPA）已作为Cytoscape应用程序开发出来，以便能够以网络方式分析GWAS数据。用户可以轻松导入GWAS汇总级数据，绘制曼哈顿图，定义模块，通过带重启的随机游走对基因进行优先级排序，检测富集的子网，并通过用户友好的界面测试子网的显著性。