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

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.

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 R and python.

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

# processed regulons
decoupleR::get_collectri(organism='human', split_complexes=FALSE)

# raw regulons
OmnipathR::collectri(organism=9606L, genesymbols=TRUE, loops=TRUE)

# processed regulons
import decoupler as dc
dc.get_collectri(organism='human', split_complexes=False)

# raw regulons
import omnipath as op
op.interactions.CollecTRI.get(genesymbols=True, organism=9606L, loops=True)

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:

• Construction of CollecTRI regulons
• Benchmark
  • Systematic comparison
  • Evaluation of binding weights
  • Statistical evaluation
• Case study
• Manuscript figures

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