mmc.threshold()

mmochi.thresholding.threshold(markname, adata, data_key=utils.DATA_KEY, preset_threshold=None, include_zeroes=False, n=0, force_model=False, plot=True, title_addition='', interactive=True, fancy=False, run=False, bins=100, external_holdout=False, key_added='lin')

Performs thresholding for marker, displays expression distribution (colored by “pos”, “?”, and “neg”) for visualization and interactive adjustment, and optionally returns thresholds and thresholded events. Thresholded events are returned as a list of “pos” for positive (at or above the higher threshold), “neg” for negative (at or below the lower threshold), and “?” for undefined (between the two thresholds). Uses utils.get_data() to identify the data to threshold.

Parameters:

  • markname (str) – Name of the marker being used. Markers can also have “_lo” or “_hi” appended to them to specify multiple thresholds on the same marker at the same level.

  • adata (AnnData) – AnnData object for creating thresholds, containing expression in the .X and/or the .obsm[data_key].

  • data_key (Union[str, list, None] (default: utils.DATA_KEY)) – Name of the key in .obsm or .var[utils.MODALITY_COLUMN] to look for when searching for markname. See utils.get_data for details on how searching is performed.

  • present_threshold – Max and minimum thresholds to apply for positive and negative populations, overrides automated calculation

  • included_zeroes – Whether to include zeroe expression values when calculating the Gaussian mixture model.

  • n (int (default: 0)) – Determines the number of Gaussians to fit. Can be 1, 2, or 3.

  • force_model (bool (default: False)) – Whether to force the creation of a Gaussian mixture model. If preset thresholds are defined, this model is only used to create msw.

  • plot (bool (default: True)) – Whether to display histograms of expression distribution with Gaussian mixes overlayed.

  • title_addition (str (default: '')) – Other information you would like to include in the title after the marker name

  • interactive (bool (default: True)) – Whether to prompt the user to enter thresholds (uses defaults if invalid entry)

  • fancy (bool (default: False)) – Whether to create adjustable float sliders to enter thresholds. Returns a list of float sliders. This should only be used by the run_all_thresholds command.

  • run (bool (default: False)) – Whether to run the thresholding to return thresholded data

  • bins (int (default: 100)) – The number of bins to plot in the histogram

  • external_holdout (bool (default: False)) – If external hold out was defined in adata.obsm[key_added], removes external hold out from threshold calculations and from graphs used for manual thresholding

  • key_added (str (default: 'lin')) – If external_holdout is true, the place in adata.obsm[key_added] to search for the external hold out column (bool T F column used to indicate whether an event should be set aside for hold out)

Return type:

Union[Tuple[float, float], Tuple[Tuple[float, float], List[str]]]

Returns:

  • thresh – Threshold values (numerics)

  • thresholded – if run == true returns thresholded data index aligned to thresh, with values of “pos”, “neg”, and “?”.