HierarchicalHotNet.jl package

HierarchicalHotNet.jl implements Hierarchical HotNet algorithm (see the original paper by M.A. Reyna et al (2018)) with a few permormance optimization and additional features.

Introduction

Network-based analysis is a powerful bioinformatic tool to put high-throughput experimental data in the context of current knowledge of cellular interactions and identify potential connections between the perturbed genes.

Workflow

• load the network of gene/protein functional interactions, e.g. ReactomeFI or STRING protein links.
• use experimental data to assign weights to the genes/proteins in the network
• generate randomized data by reshuffling node weights
• apply random walk with restart to get the stationary distribution of vertex visiting probabilities and edge transition probabilities
• use random walk-based weighted graphs to generate trees of Strongly Connected Components
• analyze the distribution of SCC metrics at each cutting threshold for read data-based SCC tree and the randomized ones
• cut the SCC tree at the optimal edge threshold and export the result as a collection of data frames