HTS-Net: An integrated regulome-interactome approach for establishing network regulation models in high-throughput screenings

PLoS One. 2017 Sep 26;12(9):e0185400. doi: 10.1371/journal.pone.0185400. eCollection 2017.

Abstract

High-throughput RNAi screenings (HTS) allow quantifying the impact of the deletion of each gene in any particular function, from virus-host interactions to cell differentiation. However, there has been less development for functional analysis tools dedicated to RNAi analyses. HTS-Net, a network-based analysis program, was developed to identify gene regulatory modules impacted in high-throughput screenings, by integrating transcription factors-target genes interaction data (regulome) and protein-protein interaction networks (interactome) on top of screening z-scores. HTS-Net produces exhaustive HTML reports for results navigation and exploration. HTS-Net is a new pipeline for RNA interference screening analyses that proves better performance than simple gene rankings by z-scores, by re-prioritizing genes and replacing them in their biological context, as shown by the three studies that we reanalyzed. Formatted input data for the three studied datasets, source code and web site for testing the system are available from the companion web site at http://htsnet.marseille.inserm.fr/. We also compared our program with existing algorithms (CARD and hotnet2).

Publication types

  • Validation Study

MeSH terms

  • Algorithms
  • Cell Differentiation
  • Databases, Genetic
  • Embryonic Stem Cells / cytology
  • Gene Regulatory Networks*
  • Hepacivirus / physiology
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • Models, Genetic*
  • Programming Languages
  • RNA Interference
  • Virus Replication

Grants and funding

Institut National du Cancer (FR) grant INCA_5911 to Christophe Ginestier and Ghislain Bidaut funded the project.