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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
.pdf
Plotting: pl
Plotting:
pl
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