NetworkHub: Prioritizing hub gene node regulation with intra-network association

Citation: Chang, H., Chu, C., Lin, S. et al. Network hub-node prioritization of gene regulation with intra-network association. BMC Bioinformatics 21, 101 (2020). https://doi.org/10.1186/s12859-020-3444-7

Overview

NetworkHub is a tool for identifying the influential hub genes in a gene-set or pathway. The method is described in detail in Hung-Ching Chang, Chiao-Pei Chu, Shu-Ju Lin, Chuhsing Kate Hsiao (2019) NetworkHub: Prioritize hub gene node regulation with intra-network association.

Tutorials

• There are 7 functions, one R markdown document and two datasets used in the example Example_of_NetworkHub.
• Manual pages Example_of_NetworkHub are good places to start with. It demonstrates a complete test run with an example. PDF file
• NetworkHub is the major function. link

Introduction to functions

• Pre-processing
  1. KGML_to_Matrix is responsible for transferring the KGML file to a directed adjacency matrix.
  2. trans2undirected is a function for transferring a directed adjacency matrix to an undirected adjacency matrix.
  3. sub_expression_data transforms the expression data from the gene level to the node level.
  4. remove_missing_node can remove nodes whose expression levels were not measured.
• Intra-network analysis
  1. The major function NetworkHub is a pathway analysis for gene expressions.
  2. rank_node ranks the nodes inside the target pathway.
• Pathway test
  1. pathway_permute performs the pathway association test with the p-value calculated by permutation.