Python script

  • Example python script running GRNBoost2 on files located in the same folder.

    <arboreto repo>/resources/dream5/net1/run_grnboost2.py
    import pandas as pd
    from distributed import Client, LocalCluster
    from arboreto.utils import load_tf_names
    from arboreto.algo import grnboost2
    if __name__ == '__main__':
        in_file  = 'net1_expression_data.tsv'
        tf_file  = 'net1_transcription_factors.tsv'
        out_file = 'net1_grn_output.tsv'
        # ex_matrix is a DataFrame with gene names as column names
        ex_matrix = pd.read_csv(in_file, sep='\t')
        # tf_names is read using a utility function included in Arboreto
        tf_names = load_tf_names(tf_file)
        # instantiate a custom Dask distributed Client
        client = Client(LocalCluster())
        # compute the GRN
        network = grnboost2(expression_data=ex_matrix,
        # write the GRN to file
        network.to_csv(out_file, sep='\t', index=False, header=False)

    Run as a classic python script:

    cd <arboreto repo>/resources/dream5/net1
    python run_grnboost2

Jupyter notebooks

Following are links to example Jupyter notebooks that illustrate different Arboreto usage scenarios (links render notebooks in Jupyter nbviewer).