SkillAgentSearch skills...

CollecTRI

Gene regulatory network containing signed transcription factor-target gene interactions

Install / Use

/learn @saezlab/CollecTRI
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

CollecTRI: Collection of Transcriptional Regulatory Interactions <img src="man/figures/CollecTRI_logo.png" align="right" width="120" />

<!-- badges: start --> <!-- badges: end -->

Overview

The CollecTRI-derived regulons contain signed transcription factor (TF) - target gene interactions compiled from 12 different resources. This collection provides an increased coverage of transcription factors and was benchmarked against other known GRNs, showing a superior performance in identifying perturbed TFs based on gene expression data using the knockTF data sets.

<p align="center" width="100%"> <img src="man/figures/overview.png" align="center" width="550"> </p>

Data availability

The CollecTRI regulons are available in the DoRothEA and decoupler packages through OmniPath.

A tutorial on how to perform TF activity estimation using CollecTRI is available in python (recommended) and in R (deprecated).

To load the CollecTRI regulons through python or R you can use the following lines:

import decoupler as dc
dc.op.collectri(organism='human')
decoupleR::get_collectri(organism='human', split_complexes=FALSE)

Resources included in CollecTRI

ExTRI, HTRI, TRRUST, TFActS, IntAct, SIGNOR, CytReg, GEREDB, Pavlidis, DoRothEA A, NTNU curations

Scripts

For more information about the CollecTRI-derived regulons, please check out the following scripts:

If you are interested in the construction of the CollecTRI meta-resource check out this repository

License

The CollecTRI-derived regulons are freely available. The original licenses of all resources included in CollecTRI can be found here

Citation

Müller-Dott, S., Tsirvouli, E., Vazquez, M., Ramirez Flores, R. O., Badia-I-Mompel, P., Fallegger, R., Türei, D., Lægreid, A., & Saez-Rodriguez, J. (2023). Expanding the coverage of regulons from high-confidence prior knowledge for accurate estimation of transcription factor activities. Nucleic Acids Research. https://doi.org/10.1093/nar/gkad841

Related Skills

View on GitHub
GitHub Stars104
CategoryDevelopment
Updated17h ago
Forks9

Languages

R

Security Score

95/100

Audited on Mar 26, 2026

No findings