CollecTRI

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Gene regulatory network containing signed transcription factor-target gene interactions

CollecTRI 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

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# CollecTRI: **Collec**tion of **T**ranscriptional **R**egulatory **I**nteractions <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](https://saezlab.github.io/dorothea/) and [decoupler](https://decoupler-py.readthedocs.io/) packages through [OmniPath](https://omnipathdb.org/).

A tutorial on how to perform TF activity estimation using CollecTRI is available in [python](https://decoupler-py.readthedocs.io/en/latest/notebooks/scell/rna_sc.html#transcription-factor-scoring-from-gene-regulatory-networks) (recommended) and in [R](https://saezlab.github.io/decoupleR/articles/tf_bk.html) (deprecated).

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

```python
import decoupler as dc
dc.op.collectri(organism='human')
```

```r
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:

- [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

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