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scParadise - Home
  • Installation
  • Tutorials
    • scAdam
      • Predict cell types with the scAdam model hub
      • Unknown cell type identification using scAdam
      • Training a custom scAdam model
      • scAdam model optimization
      • Managing large and complex training datasets
    • scEve
      • Using scEve to improve clustering
      • Custom scEve model training and optimization
      • Cross-species modality prediction using scEve
    • scNoah
      • scAdam model explainability
  • Models
    • scAdam models
    • scEve models
  • API reference
    • scAdam
      • scparadise.scadam.available_models
      • scparadise.scadam.download_model
      • scparadise.scadam.train
      • scparadise.scadam.warm_start
      • scparadise.scadam.hyperparameter_tuning
      • scparadise.scadam.train_tuned
      • scparadise.scadam.predict
    • scEve
      • scparadise.sceve.available_models
      • scparadise.sceve.download_model
      • scparadise.sceve.train
      • scparadise.sceve.hyperparameter_tuning
      • scparadise.sceve.train_tuned
      • scparadise.sceve.predict
    • scNoah
      • scparadise.scnoah.balance
      • scparadise.scnoah.oversample
      • scparadise.scnoah.undersample
      • scparadise.scnoah.report_classif_full
      • scparadise.scnoah.report_classif_sens_spec
      • scparadise.scnoah.conf_matrix
      • scparadise.scnoah.pred_status
      • scparadise.scnoah.report_reg
      • scparadise.scnoah.regres_status
      • scparadise.scnoah.pearson_coef
      • scparadise.scnoah.spearman_coef
      • scparadise.scnoah.kendalltau_coef
      • scparadise.scnoah.cell_counter
      • scparadise.scnoah.explain
      • scparadise.scnoah.feature_importance_df
      • scparadise.scnoah.get_frac
      • scparadise.scnoah.get_samples
      • scparadise.scnoah.clust_diff
  • Theory
  • GitHub
  • References
  • Citation
  • .rst

Tutorials

Contents

  • Python notebooks
  • R notebooks are available in GitHub

Tutorials#

Python notebooks#

  • scAdam
    • Predict cell types with the scAdam model hub
    • Unknown cell type identification using scAdam
    • Training a custom scAdam model
    • scAdam model optimization
    • Managing large and complex training datasets
  • scEve
    • Using scEve to improve clustering
    • Custom scEve model training and optimization
    • Cross-species modality prediction using scEve
  • scNoah
    • scAdam model explainability

R notebooks are available in GitHub#

Using scAdam in R

Using scEve in R

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Installation

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scAdam

Contents
  • Python notebooks
  • R notebooks are available in GitHub

By Vadim Chechekhin

© Copyright 2026, Vadim Chechekhin.