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How to Use the TDCor Algorithm to Infer Gene Regulatory Networks from Time Series Transcriptomic Data.

Julien Lavenus1,2, Mikaël Lucas3

  • 1DIADE, Univ Montpellier, IRD, CIRAD, Montpellier, France.

Methods in Molecular Biology (Clifton, N.J.)
|November 25, 2021
PubMed
Summary

Understanding gene regulatory networks (GRN) is crucial for biology. We present TDCor, a new R package for reconstructing GRNs from time-series transcriptomic data, aiding biological discovery.

Keywords:
Gene network topologyGene regulatory network inferenceTDCor algorithmTime seriesTranscription factorsTranscriptomic

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Area of Science:

  • Genomics
  • Systems Biology
  • Bioinformatics

Background:

  • Gene functions are known, but their integrated network remains unclear.
  • Understanding gene regulatory networks (GRN) is key to biological processes like development and environmental response.
  • High-throughput -omics data offer potential for network reconstruction.

Purpose of the Study:

  • To introduce TDCor, a novel algorithm for gene regulatory network inference.
  • To provide a user-friendly R package for implementing TDCor.
  • To detail the installation and usage of the TDCor R package.

Main Methods:

  • Utilized time-series transcriptomic data for network reconstruction.
  • Developed the TDCor algorithm based on statistical inference.
  • Packaged the TDCor algorithm as an R package.

Main Results:

  • Successfully developed the TDCor algorithm for GRN inference.
  • Created a publicly available R package for TDCor.
  • Provided detailed instructions for package installation and use.

Conclusions:

  • TDCor offers a new method for reconstructing gene regulatory networks.
  • The TDCor R package facilitates the analysis of transcriptomic data.
  • This tool aids researchers in unraveling complex biological regulatory systems.