omicverse.metabol.dgca_class_bar

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omicverse.metabol.dgca_class_bar#

omicverse.metabol.dgca_class_bar(dc_df, *, ax=None, figsize=(6.0, 3.5), log=True)[source]#

Bar chart of DC-class counts (+/+, +/0, +/-, -/+, …).

Summarises the rewiring profile from omicverse.metabol.dgca(). Each pair of metabolites is assigned a class encoding the sign of their correlation in group A and group B (+, -, 0 for significant positive, significant negative, or non-significant). Symmetric reversals (+/- and -/+) get the same red colour because they’re the strongest rewiring signal; +/+ / -/- are concordant (no rewiring); 0/0 (no signal in either group) is greyed out and pushed to the right.

Parameters:

  • dc_df (pd.DataFrame) – Output of omicverse.metabol.dgca() — needs the dc_class column.

  • log (bool, default True) – Log-scale the y-axis (counts often span orders of magnitude).

  • ax (Optional[Axes] (default: None)) – Standard matplotlib hooks.

  • figsize (tuple[float, float] (default: (6.0, 3.5))) – Standard matplotlib hooks.

Return type:

(fig, ax) tuple.

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