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patpy

General

  • Installation
  • API
    • Datasets: datasets
      • patpy.datasets.combat
      • patpy.datasets.hlca
      • patpy.datasets.onek1k
      • patpy.datasets.stephenson
      • patpy.datasets.ticatlas
    • Preprocessing: pp
      • patpy.pp.prepare_data_for_phemd
      • patpy.pp.convert_cell_types_to_phemd_format
      • patpy.pp.calculate_compositional_metrics
      • patpy.pp.calculate_cell_qc_metrics
      • patpy.pp.calculate_n_cells_per_sample
      • patpy.pp.filter_small_samples
      • patpy.pp.filter_small_cell_groups
      • patpy.pp.subsample
      • patpy.pp.is_count_data
      • patpy.pp.fill_nan_distances
    • Tools: tl
      • patpy.tl.PILOT
      • patpy.tl.PILOTGMVAE
      • patpy.tl.GroupedPseudobulk
      • patpy.tl.CellGroupComposition
      • patpy.tl.MrVI
      • patpy.tl.RandomVector
      • patpy.tl.SCPoli
      • patpy.tl.Pseudobulk
      • patpy.tl.WassersteinTSNE
      • patpy.tl.DiffusionEarthMoverDistance
      • patpy.tl.MOFA
      • patpy.tl.GloScope
      • patpy.tl.GloScope_py
      • patpy.tl.SampleRepresentationMethod
      • patpy.tl.describe_metadata
      • patpy.tl.test_distances_significance
      • patpy.tl.predict_knn
      • patpy.tl.evaluate_prediction
      • patpy.tl.test_proportions
      • patpy.tl.evaluate_representation
    • Plotting: pl
  • Contributing guide
  • Changelog
  • References

Gallery

  • Tutorials
    • Benchmarking sample representation methods with patpy
    • Using supervised sample-level methods
    • Understanding sources of variation in single-cell data with GloScope
    • Patient trajectory analysis
    • Differential gene expression across condition combinations
    • Synthetic data generation
    • Statistical test for the distances between samples from case and control groups
    • Understanding age and cytomegalovirus signals in human immune cells with sample representation

About

  • GitHub
  • .md

Tutorials

Contents

  • Quick start

Tutorials#

Take a look at examples on how to use patpy for your analysis

Quick start#

Benchmarking sample representation methods with patpy
Using supervised sample-level methods
Understanding sources of variation in single-cell data with GloScope
Patient trajectory analysis
Differential gene expression across condition combinations
Synthetic data generation
Statistical test for the distances between samples from case and control groups
Understanding age and cytomegalovirus signals in human immune cells with sample representation

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References

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Benchmarking sample representation methods with patpy

Contents
  • Quick start

By Vladimir Shitov

© Copyright 2026, Vladimir Shitov..