Palantir

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

* 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

* 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`

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](https://mellon.readthedocs.io/en/latest/model.html#mellon.model.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](https://github.com/settylab/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](https://scanpy.readthedocs.io/en/stable/), 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 ([issue64](https://github.com/dpeerlab/Palantir/issues/64)), enhancing the reproducibility and reliability of Palantir.

Minor bug fixes.

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