NetAnalyzer 1.1.0

Python package for network analysis, operations and priorization.

NetAnalyzer

Python library for network analysis, operations and priorization.

This package is designed to perform various steps in network analysis and processing through a modular design. Key features include:

• Randomization: Enables randomization of both clustered and individual nodes or edges within networks.

• Projections: Simplifies network complexity by reducing the number of layers based on connections from an excluded layer. For example, it can transition from a Phenotype-Patient-Mutation network to a Patient-Mutation network, connecting layers based on common nodes between patients and mutations.

• Topological Analysis: Computes various topological metrics for nodes (e.g., degree, betweenness) and provides summary statistics for entire networks.

• Cluster analysis: Performs metrics on predefined clusters and applies clustering algorithms based on the cdlib library.

• Embedding of networks (Kernels and node2vec): Defines node similarity using methods for processing context information in networks, including classical Kernel approaches and node2vec. It also supports integration of multiple layers.

• Prioritization: Applies propagation algorithms to prioritize nodes based on similarity metrics, such as the adjacency matrix, and a set of seed nodes.

• Net plotting: Provides several tools for graphing networks from different net plotter packages (igraph, cytoscape, graphviz).

Please, cite this library as: Rojano E., Seoane-Zonjic P., Bueno-Amorós A., Perkins JR., and Ranea JAG. Revealing the Relationship Between Human Genome Regions and Pathological Phenotypes Through Network Analysis. Lecture Notes in Computer Science, DOI: 10.1007/978-3-319-56148-6_17.