`cc_mapping.thresholding`#

GMM-based thresholding package for single-cell analysis.

This package provides classes for performing Gaussian Mixture Model (GMM) based thresholding on gene expression data within AnnData objects. It supports both single-feature thresholding and sequential refinement operations.

Main Classes:: GMMThresholding: Single-feature GMM thresholding SequentialGMM: Sequential refinement (Phase 2)
Pydantic Models:: _GaussianMixtureModelInfo: GMM parameters and results storage _DecisionBoundariesModel: Decision boundary thresholds storage _SingleThresholdingEventModel: Complete thresholding event data
Base Classes:: GaussianMixtureModelBase: Shared utilities for GMM operations

Usage:

from cc_mapping.thresholding import GMMThresholding

gmm = GMMThresholding(
    adata=adata,
    feature='gene1',
    label_obs_save_str='gene1_categories'
)
gmm.fit(n_components=2)
gmm.categorize_samples(ordered_labels=['Low', 'High'])
adata = gmm.return_adata()

Tools for Gaussian Mixture Model-based thresholding to identify cell cycle phases.

Classes#

`GMMThresholding`	A class to perform Gaussian Mixture Model (GMM) based thresholding on single-feature data.
`SequentialGMM`	Sequential GMM thresholding for iterative population refinement.