scNoah
======
   
Benchmarking cell type annotation and modality prediction.

.. currentmodule:: scparadise

Balance dataset
---------------
   
Balancing dataset using your own annotation for future model training.
Oversmaple or undersample some cell types.

.. autosummary::
   :nosignatures:
   :toctree: generated/

   scnoah.balance
   scnoah.oversample
   scnoah.undersample

Annotation metrics
------------------

Test annotation method quality using confusion matrix, accuracy, balanced accuracy and calculating cell type specific precision, recall (also called sensitivity), specificity, f1-score, geometric mean, and index balanced accuracy of the geometric mean.

.. autosummary::
   :nosignatures:
   :toctree: generated/

   scnoah.report_classif_full
   scnoah.report_classif_sens_spec
   scnoah.conf_matrix
   scnoah.pred_status

Regression metrics
------------------

Test modality prediction method quality using error metrics (RMSE, MedianAE, MeanAE), EVS, R² score and PC. 
Also, visualise metrics on cell embeddings.

RMSE - Root mean squared error

MeanAE - Mean absolute error

MedianAE - Median absolute error

EVS - Explained variance score

R² score - Coefficient of determination

PC - Pearson coefficient

For error metrics (RMSE, MedianAE, MeanAE): lower value - better prediction

.. autosummary::
   :nosignatures:
   :toctree: generated/

   scnoah.report_reg
   scnoah.regres_status
   scnoah.pearson_coef_prot

Count cells
-----------

Count number of cell types per sample or condition.

.. autosummary::
   :nosignatures:
   :toctree: generated/

   scnoah.cell_counter


Explanations
------------

Get explanations of gene importances in scAdam model prediction.

.. autosummary::
   :nosignatures:
   :toctree: generated/

   scnoah.explain
   scnoah.feature_importance

Managing large datasets
-----------------------
Get fraction of large dataset.

.. autosummary::
   :nosignatures:
   :toctree: generated/

   scnoah.get_frac
   scnoah.get_samples

Difference between clusters
---------------------------
Calculate Integral of absolute density difference and Mutual Information between two clusterings.

.. autosummary::
   :nosignatures:
   :toctree: generated/

   scnoah.clust_diff