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Article Dans Une Revue Scientific Reports Année : 2021

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

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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.
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hal-03358612 , version 1 (29-09-2021)

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Gabriel Jimenez-Dominguez, Patrice Ravel, Stéphan Jalaguier, Vincent Cavaillès, Jacques Colinge. An R package for generic modular response analysis and its application to estrogen and retinoic acid receptor crosstalk. Scientific Reports, 2021, 11 (1), ⟨10.1038/s41598-021-86544-0⟩. ⟨hal-03358612⟩
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