Simplified_InPheRNo_Pipeline

Simplified Inference of Phenotype-relevant Regulatory Networks

This is the Knowledge Engine for Genomics (KnowEnG), an NIH BD2K Center of Excellence, Simplified InPheRNo Pipeline.

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Input Files

Example Data File	Requirements
/TF_Ensemble.csv	csv/tsv, no-header - names of regulators (TFs)
/Pvalue_gene_phenotype_interest.csv	csv/tsv, genes x 1-p-value (with header)
/expr_sample.csv	csv/tsv, gene/TF x samples

Output Files

Example Data File	Format
/Network_statistic.csv	csv, genes x genes
/Network_pvalue.csv	csv genes x genes

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How to install and run this pipeline with the example data.

1. Clone this repository to your directory with all KnowEnG python3 libraries installed.

git clone https://github.com/dlanier/Simplified_InPheRNo_Pipeline.git

2. Change to the Simplified_InPheRNo_Pipeline/test directory.

cd Simplified_InPheRNo_Pipeline/test

3. Set up the environment.

make env_setup

4. Run the default data to test the installation.

make run_InPheRNo_simplified

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How to run with your data:

1. Use steps 1 - 3 above to setup the environment and place the template yaml file in the run_directory.

2. Edit the yaml file to reflect your input and output directory and input file names.

3. Run step 4 above.

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Run with docker

Simplified InPheRNo Pipeline on Docker Hub