cRegulon

Introduction

This is cRegulon software: an optimization model to identify combinatorial regulon from single cell expression and chromatin accessibility data.

Requirements:

1. Python >=3.0 with packages: numpy, sklearn, and scipy
   
2. matlab >= 2021
3. Homer

Installing cRegulon with the following command:

wget https://github.com/fengzhanying/cRegulon/archive/master.zip
unzip master.zip
cd cRegulon-master
wget https://www.dropbox.com/s/0h1wxlu7iqheajo/cRegulon.tar.gz
tar -xzvf cRegulon.tar.gz

Training mode of cRegulon

Input single cell data

The typic input file (CL_scRNA.txt) of scRNA-seq data is a gene by cell count matrix:

scRNA	RNACell1	RNACell2	RNACell3
Gene1	5	0	3
Gene2	0	2	0
Gene3	1	0	0

The typic input file (CL_scATAC.txt) of scATAC-seq data is a peak by cell count matrix:

scATAC	ATACell1	ATACell2	ATACell3	ATACell4
Peak1	1	0	1	0
Peak2	0	1	0	1
Peak3	1	0	0	0

The peaks are in the format of "chr_start_end".

Input cell type meta data

The typic cell type meta file (CL_scRNA_Cluster.txt) of scRNA-seq data is as follows:

RNACell1	C1
RNACell2	C2
RNACell3	C3

The typic cell type meta file (CL_scATAC_Cluster.txt) of scATAC-seq data is as follows:

ATACell1	C2
ATACell2	C3
ATACell3	C1
ATACell4	C2

Step 1: GRN construction

We run the following script to construct regulatory network for each cell cluster (current we support hg38 and mm10):

source runNet.sh CL hg38

This process will produce GRN files (network.txt, TFName.txt, TGName.txt, TRS.txt) for each cell cluster.

Step 2: Running cRegulon model

We run the following script of cRegulon model:

python cRegulon.py CL hg38

This will output:

1. TF combinatorial effects in each cRegulon: X.txt
   
2. Association matrix between cell clusters and cRegulons: A.txt
   
3. TF module of each cRegulon: TFs (*TF.txt) and TF pairs (*TFPair.txt).
4. Regulatory sub-network of each cRegulon: *SubNet.txt

Annotation mode of cRegulon

We run the following script to annotate cells of certain cell type:

python Annot.py CL

Citation:

If you use cRegulon software or cRegulon associated concepts, please cite:

Zhanying Feng, et al. Modeling combinatorial regulation from single-cell multi-omics provides units underpinning cell type landscape. 2024.