networkcommons.methods.run_moon_core

networkcommons.methods.run_moon_core(upstream_input=None, downstream_input=None, graph=None, n_layers=None, n_perm=1000, downstream_cutoff=0, statistic='ulm')

Runs the MOON algorithm to iteratively infer MOON scores from downstream nodes.

Parameters:

  • upstream_input (dict, optional) – Dictionary containing upstream input

  • None. (data. Defaults to)

  • downstream_input (dict) – Dictionary containing downstream input data.

  • meta_network (networkx.DiGraph) – Graph representing the regulatory

  • network.

  • n_layers (int) – Number of layers to run the MOON algorithm.

  • n_perm (int) – Number of permutations for statistical testing. Defaults

  • 1000. (to)

  • downstream_cutoff (float) – Cutoff value for downstream input scores.

  • 0. (Defaults to)

  • statistic (str) – Statistic to use for scoring. Can be “ulm”

  • "wmean" ((univariate linear model) or)

Returns:

DataFrame containing the decoupled regulatory network.

Return type:

pandas.DataFrame