Scientific Reports (Mar 2021)

An R package for generic modular response analysis and its application to estrogen and retinoic acid receptor crosstalk

  • Gabriel Jimenez-Dominguez,
  • Patrice Ravel,
  • Stéphan Jalaguier,
  • Vincent Cavaillès,
  • Jacques Colinge

DOI
https://doi.org/10.1038/s41598-021-86544-0
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 14

Abstract

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Abstract Modular response analysis (MRA) is a widely used inference technique developed to uncover directions and strengths of connections in molecular networks under a steady-state condition by means of perturbation experiments. We devised several extensions of this methodology to search genomic data for new associations with a biological network inferred by MRA, to improve the predictive accuracy of MRA-inferred networks, and to estimate confidence intervals of MRA parameters from datasets with low numbers of replicates. The classical MRA computations and their extensions were implemented in a freely available R package called aiMeRA ( https://github.com/bioinfo-ircm/aiMeRA/ ). We illustrated the application of our package by assessing the crosstalk between estrogen and retinoic acid receptors, two nuclear receptors implicated in several hormone-driven cancers, such as breast cancer. Based on new data generated for this study, our analysis revealed potential cross-inhibition mediated by the shared corepressors NRIP1 and LCoR. We designed aiMeRA for non-specialists and to allow biologists to perform their own analyses.