HIR V2: a human interactome resource for the biological interpretation of differentially expressed genes via gene set linkage analysis

Author:

Guo Wen-Ping1,Ding Xiao-Bao1,Jin Jie1,Zhang Hai-bo1,Yang Qiao-lei2,Chen Peng-Cheng2,Yao Heng2,Ruan L i1,Tao Yu-Tian1,Chen Xin123

Affiliation:

1. Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics and Information Engineering, Taizhou University, 1139 Shifu Avenue, Taizhou City, Zhejiang Province, Taizhou 318000, China

2. Institute of Pharmaceutical Biotechnology and the First Affiliated Hospital Department of Radiation Oncology, Zhejiang University School of Medicine, 866 Yuhangtang Road, Xihu District, Hangzhou City, Zhejiang Province, Hangzhou 310058, China

3. Joint Institute for Genetics and Genome Medicine between Zhejiang University and University of Toronto, Zhejiang University, 866 Yuhangtang Road, Xihu District, Hangzhou City, Zhejiang Province, Hangzhou 310058, China

Abstract

Abstract To facilitate biomedical studies of disease mechanisms, a high-quality interactome that connects functionally related genes is needed to help investigators formulate pathway hypotheses and to interpret the biological logic of a phenotype at the biological process level. Interactions in the updated version of the human interactome resource (HIR V2) were inferred from 36 mathematical characterizations of six types of data that suggest functional associations between genes. This update of the HIR consists of 88 069 pairs of genes (23.2% functional interactions of HIR V2 are in common with the previous version of HIR), representing functional associations that are of strengths similar to those between well-studied protein interactions. Among these functional interactions, 57% may represent protein interactions, which are expected to cover 32% of the true human protein interactome. The gene set linkage analysis (GSLA) tool is developed based on the high-quality HIR V2 to identify the potential functional impacts of the observed transcriptomic changes, helping to elucidate their biological significance and complementing the currently widely used enrichment-based gene set interpretation tools. A case study shows that the annotations reported by the HIR V2/GSLA system are more comprehensive and concise compared to those obtained by the widely used gene set annotation tools such as PANTHER and DAVID. The HIR V2 and GSLA are available at http://human.biomedtzc.cn.

Funder

National Natural Science Foundation of China

Science and technology project of Taizhou City

Humanities and Social Science Project of the Chinese Ministry of Education

Research project of education department of zhejiang province

Publisher

Oxford University Press (OUP)

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,Information Systems

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