iDINGO—integrative differential network analysis in genomics with Shiny application | Zendy

Caleb A. Class | Zendy; Min Jin Ha | Zendy; Veerabhadran Baladandayuthapani | Zendy; KimAnh Do | Zendy

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iDINGO—integrative differential network analysis in genomics with Shiny application

Author(s) -

Caleb A. Class,

Min Jin Ha,

Veerabhadran Baladandayuthapani,

KimAnh Do

Publication year - 2017

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btx750

Subject(s) - computer science , visualization , differential (mechanical device) , identification (biology) , hierarchy , data mining , data visualization , data science , biology , economics , engineering , market economy , aerospace engineering , botany

Differential network analysis is an important way to understand network rewiring involved in disease progression and development. Building differential networks from multiple 'omics data provides insight into the holistic differences of the interactive system under different patient-specific groups. DINGO was developed to infer group-specific dependencies and build differential networks. However, DINGO and other existing tools are limited to analyze data arising from a single platform, and modeling each of the multiple 'omics data independently does not account for the hierarchical structure of the data.

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