SJARACNe is a scalable solution of ARACNe that dramatically improves the computational performance, especially on the memory usage to allow even researchers with modest computational power to generate networks from thousands of samples. The algorithm uses adaptive partitioning mutual information to calculate the correlation between all pairs of genes to reconstruct the regulatory network.
git clone https://github.com/jyyulab/SJARACNe # Clone the repo
- Python==3.7.6
- numpy==1.20.1
- scipy==1.6.1
- pandas==1.2.3
- cwltool>=3.0.20201117141248
- node.js>=4.4.4 (required by cwltool to run locally)
- cwlexec==0.2.2 (CWL engine to run on IBM LSF)
The recommended method of setting up the required Python environment and dependencies is to use the conda dependency manager:
$ conda create -n py376 python=3.7.6
$ source activate py376Depends on the runtime environment, node.js may be installed manually to run cwltool locally; cwlexec may be installed manually to run on IBM LSF platform.
There are two options to install SJARACNe and its dependencies:
$ pip install SJARACNe
$ git clone https://github.com/jyyulab/SJARACNe
$ cd SJARACNe
$ python setup.py build # build SJARACNe binary
$ python setup.py installSJARACNe workflow is implemented in Common Workflow Language. Install node.js for running locally using cwltool; install cwlexec to run on IBM LSF platform. Users may check Common Workflow Language site for available workflow engines to run on other platforms, e.g., Toil.
usage: sjaracne [-h] {local,lsf} ...
SJARACNe is a scalable tool for gene network reverse engineering.
optional arguments:
-h, --help show this help message and exit
Subcommands:
{local,lsf} platforms
local run cwltool in a local workstation
lsf run cwlexec as in a IBM LSf cluster
sjaracne workflow is implemented with CWL. It supports multiple
computing platforms. We have tested it locally using cwltool
and on an IBM LSF cluster using cwlexec.
For the convenience, a python wrapper is developed for you to choose computing platform using subcommand.
The local mode (sjaracne local) runs in parallel by default using cwltool's --parallel option. To run it in serial, use --serial option.
To use LSF mode, editing the LSF-specific configuration file SJARACNe/config/config_cwlexec.json to change the default queue and adjust memory reservation for each step is necessary. Consider increasing memory reservation for bootstrap step and consensus step if the dimension of your expression matrix file is large.
The main input for SJARACNe is a tab-separated genes/protein by cells/samples expression matrix
with the first two columns being ID and symbol. The second required input file is the list of
significant genes/proteins IDs to be considered as hubs in the reconstructed network (the most recent version of curated
transcription factors and signaling proteins can be found in ./SJARACNe/config/TF_list.txt and ./SJARACNe/config/SIG_list.txt, respectively).
An output directory is required for storing output files. Additional parameters (e.g., LSF queue) for running on different platforms are required.
Those are available in the helping information of the corresponding subcommands, e.g., sjaracne lsf -h.
The main output of SJARACNe is a network file, which is a tab delimited text file with the following columns: source, target, mutual information, Pearson and Spearman correlations coefficients, regression line slope and p-value. SJARACNe also outputs two meta information files: parameter_info_.txt and bootstrap_info_.txt, which stores SJARACNe input parameters and bootstrap parameters respectively.
Note: for testing purpose, the number of bootstraps (-n) is set to 2, the consensus p-value threshold
-pc is set to 1.0 in the following examples. -n 100 and -pc 1e-5 are recommended for real
applications. Note that there is no / at the end of the -o option but there is a / at the end of the -tmp option.
sjaracne local -e ./test_data/inputs/BRCA100.exp -g ./test_data/inputs/tf.txt -n 2 -o ./test_data/outputs/cwl/cwltool/SJARACNE_out.final -pc 1.0 -tmp ./test_data/outputs/cwl/cwltool/tmp/
sjaracne lsf -j ./SJARACNe/config/config_cwlexec.json -e ./test_data/inputs/BRCA100.exp -g ./test_data/inputs/tf.txt -n 2 -o ./test_data/outputs/cwl/cwltool/SJARACNE_out.final -pc 1.0
Alireza Khatamian, Evan O. Paull, Andrea Califano* & Jiyang Yu*. SJARACNe: a scalable software tool for gene network reverse engineering from big data. Bioinformatics (2018). *Corresponding authors.
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