BioNetStat: A Tool for Biological Networks Differential Analysis

Author(s)

Jardim, Vinicius Carvalho ^{[1, 2]} ; Santos, Suzana de Siqueira ^[1] ; Fujita, Andre ^[1] ; Buckeridge, Marcos Silveira ^[2]

Affiliation

^[1] Univ Sao Paulo, Inst Math & Stat, Dept Comp Sci, Sao Paulo - Brazil

^[2] Univ Sao Paulo, Inst Biosci, Dept Bot, Sao Paulo - Brazil

• Document type: Journal article
• Source: FRONTIERS IN GENETICS; v. 10, JUN 21 2019.
• Web of Science Citations: 0

Abstract

The study of interactions among biological components can be carried out by using methods grounded on network theory. Most of these methods focus on the comparison of two biological networks (e.g., control vs. disease). However, biological systems often present more than two biological states (e.g., tumor grades). To compare two or more networks simultaneously, we developed BioNetStat, a Bioconductor package with a user-friendly graphical interface. BioNetStat compares correlation networks based on the probability distribution of a feature of the graph (e.g., centrality measures). The analysis of the structural alterations on the network reveals significant modifications in the system. For example, the analysis of centrality measures provides information about how the relevance of the nodes changes among the biological states. We evaluated the performance of BioNetStat in both, toy models and two case studies. The latter related to gene expression of tumor cells and plant metabolism. Results based on simulated scenarios suggest that the statistical power of BioNetStat is less sensitive to the increase of the number of networks than Gene Set Coexpression Analysis (GSCA). Also, besides being able to identify nodes with modified centralities, BioNetStat identified altered networks associated with signaling pathways that were not identified by other methods. (AU)

• FAPESP's process: 14/50884-5 - INCT 2014: National Institute of Science and Technology of Bioethanol
• Grantee: Marcos Silveira Buckeridge
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 18/21934-5 - Network statistics: theory, methods, and applications
• Grantee: André Fujita
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 16/13422-9 - Statistical methods in graphs with applications to life sciences
• Grantee: André Fujita
• Support Opportunities: Regular Research Grants
• FAPESP's process: 15/21162-4 - Identification of variables associated with the graph structure and applications in neuroscience
• Grantee: Suzana de Siqueira Santos
• Support Opportunities: Scholarships in Brazil - Doctorate
• FAPESP's process: 08/57908-6 - National Institute of Science and Technology of Bioethanol
• Grantee: Marcos Silveira Buckeridge
• Support Opportunities: Program for Research on Bioenergy (BIOEN) - Thematic Grants