signet

signet detects subnetworks under polygenic selection within biological pathways by analyzing gene interaction networks using an R package implementation.

Key Features:

• R package implementation: Provided as an R package for analysis of gene networks and pathway data.
• Subnetwork detection: Identifies subnetworks within biological pathways where multiple interacting genes exhibit unusual evolutionary features.
• Combinatorial optimization: Employs simulated annealing to search for high-scoring subnetworks within pathways.
• Network-level analysis: Moves beyond locus-level tests to assess network-level properties of interacting genes.
• Polygenic selection detection: Enhances detection of polygenic selection signals compared with classical gene-level tests.
• Candidate gene and process identification: Highlights new candidate genes and biological processes implicated in adaptation.

Scientific Applications:

• Polygenic selection mapping: Detection of polygenic selection acting on biological pathways.
• Complex trait evolution: Analysis of the network basis of adaptive traits and complex phenotypes.
• Human high-altitude adaptation: Applied to study human adaptation to high-altitude environments to reveal polygenic bases.
• Genome-wide interpretation: Interpretation of genome-wide data through gene network and pathway analysis.

Methodology:

Implements combinatorial optimization using simulated annealing to search for high-scoring subnetworks within biological pathways from gene network data, implemented in R.