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SCENIC is an R package to infer Gene Regulatory Networks and cell types from single-cell RNA-seq data.

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SCENIC (Single-Cell rEgulatory Network Inference and Clustering) is a computational method to infer Gene Regulatory Networks and cell types from single-cell RNA-seq data.

The description of the method and some usage examples are available in Nature Methods (2017).

There are currently implementations of SCENIC in R (this repository), and in Python. If you don't have a strong prefference for running it in R, we would recommend to check out the SCENIC protocol repository, which contains the Nextflow workflow, and Python/Jupyter notebooks to easily run SCENIC (highly recommended for running it in batch or bigger datasets).

For more details and installation instructions on running SCENIC in

see the tutorials: - Introduction and setup - running SCENIC

The output from the examples is available at:

Frequently asked questions: FAQ


2020/06/26: - The SCENICprotocol including the Nextflow workflow, and

notebooks are now officially released. For details see the Github repository, and the associated publication in Nature Protocols.

2019/01/24: - Tutorial for importing pySCENIC results in SCENIC by using loom files.

2018/06/20: - Added function

(see - Version bump to 1.0.

2018/06/01: - Updated SCENIC pipeline to support the new version of RcisTarget and AUCell.

2018/05/01: - RcisTarget is now available in Bioconductor. - The new databases can be downloaded from

2018/03/30: New releases - pySCENIC: lightning-fast python implementation of the SCENIC pipeline. - Arboreto package including GRNBoost2 and scalable GENIE3: - Easy to install Python library that supports distributed computing. - It allows fast co-expression module inference (Step1) on large datasets, compatible with both, the R and python implementations of SCENIC. - Drosophila databases for RcisTarget.

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