| Added by | jacques.colinge |
|---|---|
| Group name | EquipeJC |
| Item Type | Journal Article |
| Title | An R package for generic modular response analysis and its application to estrogen and retinoic acid receptor crosstalk |
| Creator | Jimenez-Dominguez et al. |
| Author | Gabriel Jimenez-Dominguez |
| Author | Patrice Ravel |
| Author | Stéphan Jalaguier |
| Author | Vincent Cavaillès |
| Author | Jacques Colinge |
| 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. |
| Publication | Scientific Reports |
| Volume | 11 |
| Issue | 1 |
| Pages | 7272 |
| Date | 2021-03-31 |
| Journal Abbr | Sci Rep |
| Language | en |
| DOI | 10.1038/s41598-021-86544-0 |
| ISSN | 2045-2322 |
| URL | https://www.nature.com/articles/s41598-021-86544-0 |
| Accessed | 2021/07/02 - 20:00:59 |
| Library Catalog | www.nature.com |
| Rights | 2021 The Author(s) |
| Extra | Bandiera_abtest: a Cc_license_type: cc_by Cg_type: Nature Research Journals Number: 1 Primary_atype: Research Publisher: Nature Publishing Group Subject_term: Computational biology and bioinformatics;Computational models;Gene regulatory networks;Genome informatics Subject_term_id: computational-biology-and-bioinformatics;computational-models;gene-regulatory-networks;genome-informatics |
| Tags | corresponding, last, original, phd |
| Date Added | 2022/12/03 - 17:07:50 |
| Date Modified | 2022/12/03 - 17:07:50 |
| Notes and Attachments | Full Text PDF (Attachment) Snapshot (Attachment) |
Institut de Recherche en Cancérologie de
