BioNetStat: A Tool for Biological Networks Differential Analysis

Autor(es)

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

Afiliação do(s) autor(es)

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

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

• Tipo de documento: Artigo Científico
• Fonte: FRONTIERS IN GENETICS; v. 10, JUN 21 2019.
• Citações Web of Science: 0

Resumo

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)

• Processo FAPESP: 14/50884-5 - INCT 2014: Instituto Nacional de Ciência e Tecnologia do Bioetanol
• Beneficiário: Marcos Silveira Buckeridge
• Linha de fomento: Auxílio à Pesquisa - Temático
• Processo FAPESP: 18/21934-5 - Estatística de redes: teoria, métodos e aplicações
• Beneficiário: André Fujita
• Linha de fomento: Auxílio à Pesquisa - Temático
• Processo FAPESP: 16/13422-9 - Métodos estatísticos para grafos com aplicações em ciências da vida
• Beneficiário: André Fujita
• Linha de fomento: Auxílio à Pesquisa - Regular
• Processo FAPESP: 15/21162-4 - Identificação de variáveis associadas à estrutura de grafos e aplicações em neurociência
• Beneficiário: Suzana de Siqueira Santos
• Linha de fomento: Bolsas no Brasil - Doutorado
• Processo FAPESP: 08/57908-6 - Instituto Nacional de Biotecnologia para o Bioetanol
• Beneficiário: Marcos Silveira Buckeridge
• Linha de fomento: Auxílio à Pesquisa - Programa BIOEN - Temático