v1.3.3

• optional progress bar with progress=True in palantir.utils.run_local_variability
• avoid NaN in local variablility output
• compatibility with scanpy>=1.10.0

v1.3.2

• require python>=3.8
• implement CI for testing
• fixes for edge cases discoverd through extended testing
• implement plot_trajectory function to show trajectory on the umap
• scale pseudotime to unit intervall in anndata

v1.3.1

• implemented palantir.plot.plot_stats to plot arbitray cell-wise statistics as x-/y-positions.
• reduce memory usgae of palantir.presults.compute_gene_trends
• removed seaborn dependency
• refactor run_diffusion_maps to split out compute_kernel and diffusion_maps_from_kernel
• remove unused dependency tables

v1.3.0

New Features

• Enable an AnnData-centric workflow for improved usability and interoperability with other single-cell analysis tools.
• Introduced new utility functions
  • palantir.utils.early_cell To automate fining an early cell based on cell type and diffusion components.
  • palantir.utils.find_terminal_states To automate finding terminal cell states based on cell type and diffusion components.
  • palantir.presults.select_branch_cells To find cells associated to each branch based on fate probability.
  • palantir.plot.plot_branch_selection To inspect the cell to branch association.
  • palantir.utils.run_local_variability To compute local gene expression variability.
  • palantir.utils.run_density A wrapper for mellon.DensityEstimator.
  • palantir.utils.run_density_evaluation Evaluate computed density on a different dataset.
  • palantir.utils.run_low_density_variability. To aggregate local gene expression variability in low density.
  • palantir.plot.plot_branch. To plot branch-selected cells over pseudotime in arbitrary y-postion and coloring.
  • palantir.plot.plot_trend. To plot the gene trend ontop of palantir.plot.plot_branch.
• Added input validation for better error handling and improved user experience.
• Expanded documentation within docstrings, providing additional clarity for users and developers.

Enhancements

• Updated tutorial notebook to reflect the new workflow, guiding users through the updated processes.
• Implemented gene trend computation using Mellon, providing more robust and efficient gene trend analysis.
• Enable annotation in palantir.plot.highight_cells_on_umap.

Changes

• Replaced PhenoGraph dependency with scanpy.tl.leiden for gene trend clustering.
• Deprecated the run_tsne, determine_cell_clusters, and plot_cell_clusters functions. Use corresponding implementations from Scanpy, widely used single-cell analysis library and direct dependecy of Palantir.
• Rename palantir.plot.highight_cells_on_tsne to palantir.plot.highight_cells_on_umap
• Depend on anndata>=0.8.0 to avoid issues writing dataframes in ad.obsm.

Fixes

• Addressed the issue of variability when reproducing results (issue#64), enhancing the reproducibility and reliability of Palantir.

v1.2.0

Minor bug fixes.

v1.1.0

Replaced rpy2 with pyGAM for computing gene expression trends
Updated tutorials and plotting functions

v1.0.1

Removing multicoreTSNE dependency for installation

v1.0.0

New Release

Revamped tutorial with support for Anndata and force directed layouts

v0.2.6: Issue_33 and 31 fix

A fix related to https://github.com/dpeerlab/Palantir/issues/33 and https://github.com/dpeerlab/Palantir/issues/31

v0.2.5

Issue_28 fix

A fix related to [issue#28](https://github.com/dpeerlab/Palantir/issues/28).
When identifying terminal states, duplicate values were generated instead of unique ones.