Author:
Li Wan,Zhang Yihua,Wang Yahui,Rong Zherou,Liu Chenyu,Miao Hui,Chen Hongwei,He Yuehan,He Weiming,Chen Lina
Abstract
Abstract
Background
Identifying or prioritizing genes for chronic obstructive pulmonary disease (COPD), one type of complex disease, is particularly important for its prevention and treatment.
Methods
In this paper, a novel method was proposed to Prioritize genes using Expression information in Protein–protein interaction networks with disease risks transferred between genes (abbreviated as PEP). A weighted COPD PPI network was constructed using expression information and then COPD candidate genes were prioritized based on their corresponding disease risk scores in descending order.
Results
Further analysis demonstrated that the PEP method was robust in prioritizing disease candidate genes, and superior to other existing prioritization methods exploiting either topological or functional information. Top-ranked COPD candidate genes and their significantly enriched functions were verified to be related to COPD. The top 200 candidate genes might be potential disease genes in the diagnosis and treatment of COPD.
Conclusions
The proposed method could provide new insights to the research of prioritizing candidate genes of COPD or other complex diseases with expression information from sequencing or microarray data.
Publisher
Springer Science and Business Media LLC
Subject
Pulmonary and Respiratory Medicine
Cited by
4 articles.
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