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NetBID 2.0: Data-driven Network-based Bayesian Inference of Drivers

Documentation and Guided Analyses

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Overview

NetBID2 is a systematic, data-driven, network-based approach for revealing and characterizing “drivers” of biological interest. It can provide insights to help understand unclear biological mechanisms and can also identify potential therapeutic targets. Many “hidden drivers,” such as signaling proteins and epigenetic factors, are crucial contributors to disease phenotypes. However, the existing tools that use traditional differentiation analysis are inadequate for mining a list of “drivers” to find candidates for further investigation.

NetBID is a data-driven systems biology pipeline that uses a data-driven, network-based Bayesian inference approach to identify drivers from transcriptomics, proteomics, and phosphoproteomics data, where the drivers can be either transcription factors (TFs) or signaling factors (SIGs).

NetBID version 2.0 (shorten to NetBID2) is an upgraded version of NetBID 1.0, which has been published in Nature in 2018. NetBID 2.0 inherites all of the main functions from NetBID 1.0 and provides many more functions and pipelines with which to perform advanced end-to-end analyses.

SupFigure1

NetBID2 has the following key features, making it a handy, comprehensive and practicable software with which to perform “hidden driver” analysis.

More data processing functions:

  • Expression matrix pre-processing and quality assessment
  • SJARACNe-based network reconstruction
  • Activity calculation of drivers and gene sets
  • Discovery of differentially expressed genes and differentially activated drivers
  • Generation of the master table for drivers
  • For more data processing functions, please check NetBID2 PDF manual

More visualization functions:

  • Unsupervised learning of samples, comparison of the predicted labels vs. the observed labels
  • Display of drivers with significance profiles and target genes
  • Display of selected drivers with more details and the sub-network structure
  • For more visualization functions, please check NetBID PDF manual

More supporting functions:

  • Gene/transcript ID conversion
  • Gene function enrichment analysis and visualization
  • Data and pipeline management
  • For more supporting functions, please check NetBID PDF manual