DEGGs

DEGGs identifies differentially expressed gene-gene interactions in high-throughput sequencing datasets and quantifies differential gene-gene correlations across phenotypical groups.

Key Features:

• Differential interaction detection: Identifies differentially expressed gene-gene interactions and differential correlations between phenotypical groups from high-throughput sequencing data.
• Network Extraction: Extracts group-specific gene-gene interaction networks from provided count and design matrices.
• Statistical Analysis: Assesses each gene-gene link for differential significance using robust linear regression with an interaction term.
• Implementation: Implemented as an R package operating on count and design matrices derived from sequencing experiments.

Scientific Applications:

• Molecular mechanism analysis: Elucidates activation or deactivation of biological processes associated with specific conditions by comparing gene-gene interactions across groups.
• Genomics and systems biology: Supports analysis of regulatory interaction networks in genomics and systems biology studies.
• Biomarker and target discovery: Facilitates identification of potential biomarkers or therapeutic targets for personalized medicine by highlighting differential interactions.

Methodology:

Extracts group-specific interaction networks from count and design matrices and tests each gene-gene link for differential significance using robust linear regression with an interaction term.