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Releases: earmingol/cell2cell

v0.7.4

06 May 18:08
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Please refer to the release notes of all previous versions here

New features

Feature updates

  • Updated assert warnings for Tensor-cell2cell

Fixed Bugs

  • Fixed set indexing that was deprecated in new pandas versions (in cell2cell.preprocessing.rnaseq.add_complexes_to_expression())

What's Changed

Full Changelog: v0.7.3...v0.7.4

cell2cell - v0.7.3

29 Nov 23:16
c904946
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New features

  • Refer to v0.7.2 notes to see the previous new features.
  • Added example of using Spatial Data with Tensor-cell2cell.

Feature updates

  • Updated single-cell data example with cell2cell to use COVID-19 data.
  • Updated bulk data example with cell2cell.
  • Updated docs folder for readthedocs.org.
  • Updated README.md

Fixed Bugs

  • Fixed legend visualization in cell2cell.plotting.pcoa_plot.pcoa_3dplot()
  • Fixed negative P-values in cell2cell.stats.permutation.compute_pvalue_from_dist()
  • Fixed permutation analysis in cell2cell.analysis.cell2cell_pipelines.SingleCellInteractions
  • Fixed legend visualization in cell2cell.plotting.circular_plot.circos_plot()

cell2cell - v0.7.0 and v0.7.1

19 Nov 22:39
7b00865
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New features

  • Added cell2cell.spatial functions for enabling analyses considering spatial organization in spatial data.
    These functions include:
    • Filtering by intercellular distances by thresholding values (cell2cell.spatial.distances and cell2cell.spatial.filtering).
    • Dividing the tissue in square grids (cell2cell.spatial.neighborhoods.create_spatial_grid())
    • Dividing the tissue in moving windows (cell2cell.spatial.neighborhoods.create_sliding_windows(), cell2cell.spatial.neighborhoods.calculate_window_size(),
      and cell2cell.spatial.neighborhoods.add_sliding_window_info_to_adata())

Feature updates

Fixed Bugs

  • Fixed bug that made to incorrectly visualize multiple legends in plots as for example in cell2cell.plotting.tensor_plot
    when using newer matplotlib versions.

cell2cell - v0.6.8

20 Apr 19:51
9fa855d
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Fixed Bugs

  • Fixed bug that was skipping first factor to generate outputs from cell2cell.external.gseapy.run_gsea()

cell2cell - v0.6.7

22 Mar 05:36
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Release Notes - cell2cell v0.6.7

New features

  • Direct access to interaction_elements attribute from cell2cell.analysis.cell2cell_pipelines.SingleCellInteractions
    and cell2cell.analysis.cell2cell_pipelines.BulkInteractions
  • Added option to store GMT file in output_folder in cell2cell.external.gseapy

Feature updates

  • Removed tqdm for jupyter notebooks.
  • Updated tensorly version from 0.7.0 to 0.8.1

Fixed Bugs

  • Modified permutations in cell2cell.analysis.cell2cell_pipelines.SingleCellInteractions.permute_cell_labels()

cell2cell - v0.6.6

03 Mar 07:00
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Release Notes - cell2cell v0.6.6

New features

  • Added new attributes and methods to cell2cell.tensor.tensor.BaseTensor and any other
    derived class, including BaseTensor.shape, BaseTensor.write_file(), BaseTensor.to_device().
    These new features are respectively for:
    • Passing the shape of the tensor directly (instead of BaseTensor.tensor.shape)
    • Export or save a tensor object to a file.
    • Change the device for running Tensor-cell2cell (e.g. 'cpu', 'cuda', etc.)

Feature updates

  • Added **kwargs as parameter of cell2cell.analysis.tensor_pipelines.run_tensor_cell2cell_pipeline()
    to directly pass parameters to the functions running the elbow analysis and the tensor decomposition.
  • Sort factors numerically in cell2cell.external.gseapy.run_gsea().

Fixed Bugs

cell2cell - v0.6.5

02 Feb 02:28
0b5f671
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Release Notes - cell2cell v0.6.5

New features

  • Implemented in-house GSEA using gseapy. Associated code is located in
    cell2cell.datasets.gsea_data and cell2cell.external.gseapy.
  • Implemented a function to obtain a dataframe of lr pairs by cell pairs from a tensor decomposition
    result, so it can be use to make a plot. It can compute a communication score that is by factor or
    across all factors. See function cell2cell.analysis.tensor_downstream.get_lr_by_cell_pairs().

Feature updates

  • Added the axis names to the dataframe generated with cell2cell.analysis.tensor_downstream.get_joint_loadings(),
    which correspond to the dim1 and dim2 parameters.
  • Added the axis labels (cm.ax_heatmap.set_xlabel() & (cm.ax_heatmap.set_ylabel()) using the dataframe axis names
    passed to cell2cell.plotting.factor_plot.loading_clustermap()

What's Changed

Full Changelog: v0.6.4...v0.6.5

cell2cell - v0.6.4

21 Jan 01:10
b0c1851
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Release Notes - cell2cell v0.6.4

New features

  • Added a the cell2cell.io.read_data.load_tensor() function to directly load a previously
    exported interaction_tensor variable generated with Tensor-cell2cell.
  • Added a new dataset from a COVID-19 study. Available in cell2cell.datasets.anndata.balf_covid().
  • Added functions to create and explore directories in cell2cell.io.directories.
  • Added cell2cell.io.read_data.load_tables_from_directory() to load all tables or dataframes with the same
    extension that are located in such directory.

Feature updates

  • Modified sparsity_fraction() and missing_fraction() methods of cell2cell.tensor.tensor.BaseTensor to return
    the item in the tensorly tensor object.
  • Added progress bar to cell2cell.tensor.external_scores.dataframes_to_tensor().
  • Added the option to specify the backend when running cell2cell.analysis.tensor_pipelines.run_tensor_cell2cell_pipeline().

Fixed Bugs

  • Implemented a way to manage duplicated instances of a LR comm score in cell2cell.tensor.external_scores.dataframes_to_tensor().
    It can be controled through the parameter dup_aggregation.

What's Changed

New Contributors

Full Changelog: https://github.com/earmingol/cell2cell/commits/v0.6.4