Science Score: 10.0%
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1 of 10 committers (10.0%) from academic institutions -
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○Scientific vocabulary similarity
Low similarity (13.1%) to scientific vocabulary
Keywords
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Repository
Scalable Tool for Gene Network Reverse Engineering
Basic Info
Statistics
- Stars: 24
- Watchers: 7
- Forks: 16
- Open Issues: 9
- Releases: 3
Topics
Metadata Files
README.md
SJARACNe
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.
Download
git clone https://github.com/jyyulab/SJARACNe # Clone the repo
Prerequisites
- 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)
Create a virtual environment (recommended)
Using conda to create a virtual environment
The recommended method of setting up the required Python environment and dependencies is to use the conda dependency manager:
bash
$ conda create -n py392 python=3.9.2
$ source activate py392
Installation
Depends 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:
(Option 1) Install via pip
$ pip install SJARACNe
(Option 2) Install from source
bash
$ git clone https://github.com/jyyulab/SJARACNe
$ cd SJARACNe
$ python setup.py build # build SJARACNe binary
$ python setup.py install
Install optional packages depends on runtime platform
SJARACNe 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 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
sjaracneworkflow is implemented with [CWL](https://www.commonwl.org/). It supports multiple
computing platforms. We have tested it locally using [cwltool](https://github.com/common-workflow-language/cwltool)
and on an IBM LSF cluster using [cwlexec](https://github.com/IBMSpectrumComputing/cwlexec).
For the convenience, a python wrapper is developed for you to choose computing platform usingsubcommand```.
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.
Inputs
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/TFlist.txt and ./SJARACNe/config/SIGlist.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.
Outputs
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: parameterinfo.txt and bootstrapinfo.txt, which stores SJARACNe input parameters and bootstrap parameters respectively.
Examples to create a transcription factor network
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.
Running on a single machine (Linux/OSX)
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/
Running on an IBM LSF cluster
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
Reference
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.
Owner
- Name: Yu Laboratory @ St. Jude
- Login: jyyulab
- Kind: organization
- Location: Memphis, TN
- Website: https://www.stjude.org/research/labs/yu-lab.html
- Twitter: jiyang_yu
- Repositories: 11
- Profile: https://github.com/jyyulab
Yu Lab in the Department of Computational Biology at St. Jude Children's Research Hospital
GitHub Events
Total
- Issues event: 1
- Watch event: 1
- Member event: 1
- Issue comment event: 3
Last Year
- Issues event: 1
- Watch event: 1
- Member event: 1
- Issue comment event: 3
Committers
Last synced: almost 3 years ago
All Time
- Total Commits: 182
- Total Committers: 10
- Avg Commits per committer: 18.2
- Development Distribution Score (DDS): 0.555
Top Committers
| Name | Commits | |
|---|---|---|
| Liang Ding | a****g@g****m | 81 |
| Jimmy Veloso | j****0@y****r | 44 |
| Alireza Khatamian | a****5@g****m | 30 |
| Khatamian | a****i@d****l | 12 |
| Keith Hughitt | k****t@g****m | 8 |
| Jiyang Yu | j****u@u****m | 3 |
| Alireza | a****i@l****l | 1 |
| Alireza Khatamian | a****k@u****u | 1 |
| Qingfei Pan | 3****n@u****m | 1 |
| Lei Yan | l****n@s****g | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 45
- Total pull requests: 9
- Average time to close issues: 9 months
- Average time to close pull requests: 10 days
- Total issue authors: 30
- Total pull request authors: 3
- Average comments per issue: 1.91
- Average comments per pull request: 0.44
- Merged pull requests: 8
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 3
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 3
- Pull request authors: 0
- Average comments per issue: 2.33
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- adamdingliang (11)
- ERIGR (3)
- khughitt (3)
- guillaumecharbonnier (2)
- albertop210 (1)
- karlie002 (1)
- fossbert (1)
- MathildaStigenberg (1)
- zjgt (1)
- saisaitian (1)
- decarlin (1)
- Tangke98 (1)
- albertoriva (1)
- MingBit (1)
- jasonchian (1)
Pull Request Authors
- ZebYulon (6)
- jimmyv9 (3)
- khughitt (3)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- pypi 4 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 2
- Total maintainers: 1
pypi.org: sjaracne
Gene network reverse engineering from big data
- Homepage: https://github.com/jyyulab/SJARACNe
- Documentation: https://sjaracne.readthedocs.io/
- License: See LICENSE.md
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Latest release: 0.2.1
published about 4 years ago
Rankings
Maintainers (1)
Dependencies
- cwltool >=3.0.20201117141248
- numpy ==1.20.1
- pandas ==1.2.3
- scipy ==1.6.1
- cwltool *
- numpy *
- pandas *
- scipy *