https://github.com/saezlab/collectri
Gene regulatory network containing signed transcription factor-target gene interactions
https://github.com/saezlab/collectri
Last synced: over 1 year ago
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Gene regulatory network containing signed transcription factor-target gene interactions
- Host: GitHub
- URL: https://github.com/saezlab/collectri
- Owner: saezlab
- License: gpl-3.0
- Created: 2021-09-06T13:48:15.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2024-04-24T15:19:52.000Z (about 2 years ago)
- Last Synced: 2025-03-28T05:51:01.844Z (over 1 year ago)
- Language: R
- Homepage:
- Size: 8.05 MB
- Stars: 73
- Watchers: 7
- Forks: 7
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# CollecTRI: **Collec**tion of **T**ranscriptional **R**egulatory **I**nteractions 
## 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](https://saezlab.github.io/dorothea/) and [decoupler](https://saezlab.github.io/decoupleR/) packages through [OmniPath](https://omnipathdb.org/).
A tutorial on how to perform TF activity estimation using CollecTRI is available in [R](https://saezlab.github.io/decoupleR/articles/tf_bk.html) and [python](https://decoupler-py.readthedocs.io/en/latest/notebooks/dorothea.html).
To load the CollecTRI regulons through R or python you can use the following lines:
```r
# processed regulons
decoupleR::get_collectri(organism='human', split_complexes=FALSE)
# raw regulons
OmnipathR::collectri(organism=9606L, genesymbols=TRUE, loops=TRUE)
```
```python
# 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](https://github.com/saezlab/CollecTRI/tree/main/scripts/CollecTRI)
- [Benchmark](https://github.com/saezlab/CollecTRI/tree/main/scripts/benchmark)
- [Systematic comparison](https://github.com/saezlab/CollecTRI/blob/main/scripts/benchmark/02_benchmark.ipynb)
- [Evaluation of binding weights](https://github.com/saezlab/CollecTRI/blob/main/scripts/benchmark/03_benchmark_weights.ipynb)
- [Statistical evaluation](https://github.com/saezlab/CollecTRI/blob/main/scripts/benchmark/05_statistics.R)
- [Case study](https://github.com/saezlab/CollecTRI/blob/main/scripts/casestudy/case_study.R)
- [Manuscript figures](https://github.com/saezlab/CollecTRI/blob/main/scripts/figures/figures_manuscript.R)
If you are interested in the construction of the CollecTRI meta-resource check
out this [repository](https://github.com/Rbbt-Workflows/ExTRI)
## License
The CollecTRI-derived regulons are freely available.
The original licenses of all resources included in CollecTRI can be found [here](https://github.com/saezlab/pypath/blob/master/pypath/resources/data/resources.json)
## 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