MIDAS is a software tool that determines differentially activated subpaths from multi-class RNA-seq data.
- MIDAS utilizes explicit gene expression quantity information from RNA-seq.
- MIDAS extends a recent edge activation measurement technique for determining subpaths with differential activities.
- MIDAS uses the multi-class issue in a statistical approach.
- MIDAS uses a greedy subpath extension method with exponentially increasing criteria.
MIDAS is implemented in with Bash scripts, R, and Python libraries. Belows are requirements for MIDAS.
- Python: 2.7
- Networkx: over 1.10 (https://networkx.github.io/index.html)
- scipy: over 0.17.1 (https://www.scipy.org/)
- Statsmodels: over 0.6.1 (http://www.statsmodels.org/0.6.1/index.html)
- matplotlib: over 1.5.1 (http://matplotlib.org/)
- R: over 3.0.2
First, clone the repository or download compressed source code files.
$ git clone https://github.com/bhi-kimlab/MIDAS.git
$ cd MIDAS
You can see the valid paramenters for MIDAS by help option:
$ bash ./run.sh --help
One example of parameter setting is like:
$ bash run.sh \
--expression ./test_data/total_exp.MGD \
--pathway_set ./test_data/pathway_set.txt \
--class_info ./test_data/total_exp.MGD.sample_class.txt \
--output_directory ./test_result/ \
--start_threshold 0.05 \
--increase_moment 1e-15 \
--permutation_cutoff 0.1 \
--permutation_number 100000 \
--parallel_cores 10
You can run MIDAS with test data:
cd test
bash ./test_run.sh
If you have any question or problem, please send a email to [email protected]