calour.transforming.normalize_compositional¶

calour.transforming.normalize_compositional(exp: calour.experiment.Experiment, min_frac=0.05, total=10000, inplace=False)[source]¶

Normalize each sample by ignoring the features with mean>=min_frac in all the experiment

This assumes that the majority of features have less than min_frac mean, and that the majority of features don’t change between samples in a constant direction

Note

This function is also available as a class method Experiment.normalize_compositional()

Parameters:	exp (Experiment) – Input experiment object. min_frac (float, optional) – ignore features with mean (over all samples) >= min_frac. total (int, optional) – The total abundance for the non-excluded features per sample inplace (bool, optional) – False (default) to create a new experiment, True to normalize in place
Returns:	The normalized experiment. Note that all features are normalized (including the ones with mean>=min_frac)
Return type:	Experiment