Release notes

1.1.0 (12.04.2024)

  • Added a check for the subset of cell types in li.multi.dea_to_lr. Related to #92.

  • Split Local and Global Bivariate metrics. Specifically, I reworked completely the underlying code, though the API should remain relatively unchanged. With the exceptions of: 1) lr_bivar is now removed and bivar has been renamed to bivariate. This allowed me to remove a lot of redundancies between the two functions. 2) nz_threshold has been renamed to nz_prop for consistency with expr_prop in the remainder of the package. Related to #44.

  • li.mt.bivariate parameter mod_added has been renamed to key_added due to this now refer to both .obsm and .mod - depedening whether an AnnData or MuData object is passed.

  • Added Global [Lee’s statistic](https://onlinelibrary.wiley.com/doi/abs/10.1111/gean.12106), along with a note on weighted product that upon z-scaling it is equivalent to Lee’s local statistic.

  • The Global [L statistic](https://onlinelibrary.wiley.com/doi/abs/10.1111/gean.12106) and Global [Moran’s R](https://www.nature.com/articles/s41467-023-39608-w) are themselves basically identical. See Eq.22 from Lee and Eq.1 in Supps of SpatialDM.

  • Changed the li.mt.bivar parameter function_name to local_name for consistency and to avoid ambiguity with the newly-added global_name parameter.

  • Added bumpversion to manage versioning. Related to #73.

  • Added max_runs and stable_runs parameters to enable the inference of robust causal networks with CORNETO. Related to #82.

  • Optimized MISTy such that the matrix multiplication by weights is done only once, rather than for each target. Users can now obtain the weighted matrix via the misty.get_weighted_matrix function.

  • MISTy models are now passed externally, rather than being hardcoded. This allows for more flexibility in the models used. As an example, I also added a RobustLinearModel from statsmodels. Related to #74.

  • Removed forced conversion to sparse csr_matrix matrices in MISTy. Related to #57.

1.0.5 (25.02.2024)

  • Added ScSeqComm Method, implemented by @BaldanMatt (#68)

  • Added functions to query a metabolite-receptor interactions database ([MetalinksDB](https://github.com/biocypher/metalinks)), including:

=> li.rs.get_metalinks to get the database => li.rs.get_metalinks_values to get the distinct annotation values of the database => describe_metalinks to get a description of the database

  • Added a metabolite-mediated CCC tutorial in spatially-resolved multi-omics data (#45).

  • Changed hardcoded constants to be defined in _constants.py

  • Excluded CellChat from the default rank_aggregate method

  • Fixed return logic of SpatialBivariate

  • li.mt.process_scores is now exported to li.mt

  • Changed the default max_neighbours in li.ut.spatial_neighbors to 1/10 of the number of spots.

1.0.4 (17.01.2024)

  • Moved the Global score summaries of SpatialBivariate from .uns to .var

  • df_to_lr will now also return the expression and proportion of expression for the interactions

  • li.multi.nfm will now also accept a DataFrame as input

  • Filtered putative interactions in the Consensus resource, mostly such coming from CellTalkDB.

  • Changed filter_lambda parameter to filter_fun for consistency and now any function can be passed to be applied as a row-wise filter.

  • Global results of SpatialBivariate will now be saved to .var

  • Added li.ut.interpolate_adata utility function to interpolate the data to a common space.

  • MISTy will also work with directly non-aligned data with spatial connectivities from one modality to the other being passed via obsm rather than obsp. Making use of li.ut.spatial_neighbors by passing reference coordinates.

  • Fixed a bug where li.ut.obsm_to_adata would assign var as a method rather than DataFrame

  • Fixed a bug where p-values for Global Moran’s were not calculated correctly.

  • Enabled cell_pairs of interest to be passed to single-cell methods.

  • Enabled Parallelization of Permutation-based methods.

  • Local categories will now be only calculated for positive interactions (not non-ambigous as before).

  • Names of source and target panels can now be passed to li.pl.tileplot.

  • li.rs.explode_complexes is now consistently exported to li.rs (as previous versions)

  • li.mt.find_causalnet: changed the noise assigned to nodes to be proportional to the minimum penalty of the model. Also, added noise to the edges to avoid multiple solutions to the same problem.

1.0.3 (06.11.2023)

  • Added filterby and filter_lambda parameters to li.pl.interactions and li.pl.target_metrics to allow filtering of interactions and metrics, respectively.

  • Removed unnecessary stat parameter from li.pl.contributions

  • Added tests to ensure both lr_bivar and single-cell methods throw an exception when the resource is not covered by the data.

  • estimate_elbow will add the errors and the number of patterns to .uns when inplace is True.

  • When groupby or sample_key are not categorical liana will now print a warning before converting them to categorical. Related to #28

  • Various documentation improvements, including using docrep to ensure consistency.

  • __version__ will now correctly reflect the version in pyproject.toml

  • Exported repeated value definitions to _constants.py

  • Renamed some *_separator columns to *_sep for consistency.

  • Added li.ut.query_bandwidth to query the bandwidth of the spatial connectivities (used in spatial bivariate tutorial)

  • Added pre-commit hooks adapted from scverse’s cookiecutter.

1.0.2 (13.10.2023)

  • Added as seed param to find_causalnet, used to a small amount of noise to the nodes in to avoid obtaining multiple solutions to the same problem when multiple equal solutions are possible.

  • Updated installation.rst to refer to pip install liana[common] and liana[full] for extended installations.

  • Fixed a bug which would cause bivar to crash when an AnnData object was passed

Merged #61 including the following:

  • Added standardize parameter to spatial_neighbors, used to standardize the spatial connectivities such that each spot’s proximity weights to 1. Required for non-standardized metrics (such as product)

  • Fixed edge case in assert_covered to handle interactions not present in adata nor the resource.

  • Added simple product (scores ranging from -inf, +inf) and norm_product (scores ranging from -1, +1).

The former is a simple product of x and y, while the latter standardized each variable to be between 0 and 1, following weighing by spatial proximity, and then multiplies them. Essentially, it diminishes the effect of spatial proximity on the score, while still taking it into account. We observed that this is useful for e.g. border zones.

1.0.1 Stable Release (30.09.2023)

  • Bumped CORNETO version and it’s now installed via PyPI.

1.0.0a2 (19.09.2023)

  • Interactions names in tileplot and dotplot will now be sorted according to orderby when used; related to #55

  • Added filter_view_markers function to filter view markers considered background in MOFAcellular tutorial

  • Added keep_stats parameter to adata_to_views to enable pseudobulk stats to be kept.

  • Replace intra_groupby and extra_groupby with maskby in misty. The spots will now only be filtered according to maskby, such that both intra and extra both contain the same spots. The extra views are multiplied by the spatial connectivities prior to masking and the model being fit

  • Merge MOFAcell improvements; related to #42 and #29

  • Targets with zero variance will no longer be modeled by misty.

  • Resolve #46 - refactored misty’s pipeline

  • Resolved logging and package import verbosity issues related to #43

  • Iternal .obs[‘label’] placeholder renamed to the less generic .obs[‘@label’]; related to #53

  • Minor Readme & tutorial text improvements.

1.0.0a1 Biorxiv (30.07.2023)

  • positive_only in bivariate metrics was renamed to mask_negatives will now mask only negative-negative/low-low interactions, and not negative-positive interactions.

  • Replaced MSigDB with transcription factor activities in MISTy’s tutorial

  • Enable sorting according to ascending order in misty-related plots

  • Enable cmap to be passed to tileplot & dotplots

  • Minor Readme & tutorial improvements.

1.0.0a0 (27.07.2023) LIANA+ Release

LIANA becomes LIANA+.

Major changes have been made to the repository, however the API visible to the user should be largely consistent with previous versions, except minor exceptions: - li.fun.generate_lr_geneset is now called via li.rs.generate_lr_geneset

  • the old ‘li.funcomics’ model is now renamed to something more general: li.utils

  • get_factor_scores and get_variable_loadings were moved to li.utils

LIANA+ includes the following new features:

Spatial

how to summarize those into patterns using NMF.

  • A radial basis kernel is implemented to calculate spot/cell connectivities (spatial connectivities); this is used by the spatially-informed bivariate metrics and MISTy.

It mirrors [squidpy’s](https://squidpy.readthedocs.io/en/stable/) sq.gr.spatial_neighbors function, and is hence interchangeable with it.

Handling multiple modalities

  • LIANA+ will now work with multi-modal data, i.e. it additionally support MuData objects as well as AnnData objects.

The API visible to the user is the same, but the underlying implementation is different.

  • These come with a new tutorial that shows how to use LIANA+ with multi-modal (CITE-Seq) data, along with inbuilt transformations.

  • The same API is also adapted by the local bivariate metrics, i.e. they can also be used with multi-modal data.

Multi-conditions

  • A utility function has been added that will take any dataframe with various statistics and append it to information from AnnData objects;

thus creating a multi-condition dataframe in the format of LIANA.

  • A new tutorial that shows how to use PyDESeq2 together with this utility function has been added, essentially a tutorial on “Hypothesis-driven CCC”.

Visualizations

  • A tileplot (li.pl.tileplot) has been added to better visualize ligands and receptors independently.

  • MISTy-related visualizations have been added to vislualize view contributions and performance, and interaction coefficients/importances.

  • A simple plot li.pl.connectivity is added to show spatial connectivities

Others

  • A Causal Network inference function has been added to infer downstream signalling networks. This is currently placed in the tutorial with PyDESeq2.

  • An elbow approximation approach has been added to the NMF module, to help with the selection of the number of patterns.

  • Various utility functions to simplify AnnData extraction/conversion, Matrix transformations, etc (added to li.ut)

Note: this is just an overview of the new features, for details please refer to the tutorials, API, and documentation.

0.1.9 (06.06.2023)

  • Fixed issues with deprecated params of pandas.DataFrame.to_csv & .assert_frame_equal in tests

  • multi.get_variable_loadings will now return all factors

  • Added source & target params to fun.generate_lr_geneset

  • Refactored sc._Method._get_means_perms & related scoring functions to be more efficient.

None can now be passed to n_perms to avoid permutations - these are only relevant if specificity is assumed to be relevant.

  • LIANA’s aggregate method can now be customized to include any method of choice (added an example to basic_usage).

  • Removed ‘Steady’ aggregation from rank_aggregate

  • Changed deprecated np.float to np.float32 in liana_pipe, relevant for CellChat mat_max.

  • Method results will now be ordered by magnitude, if available, if not specificity is used.

  • Added ligand_complex and receptor_complex filtering to liana’s dotplot

  • MOFAcellular will now work only with decoupler>=1.4.0 which implements edgeR-like filtering for the views.

0.1.8 (24.03.2023)

  • Removed walrus operator to support Python 3.7

  • Added a tutorial that shows the repurposed use of MOFA with liana to obtain intercellular communication programmes, inspired by Tensor-cell2cell

  • Added a tutorial that shows the repurposed use of MOFA to the analysis of multicellular programmes as in Ramirez et al., 2023

  • Added key_added parameter to save liana results to any adata.uns`` slot, and uns_key to use liana results from any adata.uns slot

  • inplace now works as intended (i.e. only writes to adata.uns if inplace is True).

0.1.7 (08.02.2023)

  • Fixed an edge case where subunits within the same complex with identical values resulted in duplicates. These are now arbitrarily removed according to random order.

  • All methods’ complexes will now be re-assembled according to the closest stat to expression that each method uses, e.g. cellchat will use trimeans and the rest means.

  • Added a basic liana to Tensor-cell2cell tutorial as a solution to liana issue #5

  • Updated the basic tutorial

  • Referred to CCC chapter from Theis’ best-practices book

0.1.6 (23.01.2023)

  • Fixed issue with duplicate subunits for non-expressed LRs when return_all_lrs is True

  • min_prop when working with return_all_lrs is now filled with 0s

  • Added by_sample function to class Method that returns a long-format dataframe of ligand-receptors, for each sample

  • Added dotplot_by_sample function to visualize ligand-receptor interactions across samples

  • Refractored preprocessing of dotplot and dotplot_by_sample to a separate function

  • Changed “pvals” of geometric_mean method to “gmean_pvals” for consistency

  • to_tensor_c2c utility function to convert a long-format dataframe of ligand-receptor interactions by sample to Tensor-cell2cell tensor.

  • Added a list to track the instances of MethodMeta class

  • Added generate_lr_geneset function to generate a geneset of ligand-receptors for different prior knowledge databases

0.1.5 (11.01.2023)

  • Hotfix return_all_lrs specificity_rank being assigned to NaN

  • Add test to check that specificity_rank of lrs_to_keep is equal to min(specificity_rank)

0.1.4 (11.01.2023)

  • rank_aggregate will now sort interactions according to magnitude_rank.

  • Fixed SettingWithCopyWarning warning when return_all_lrs is True

  • Minor text improvements to the basic tutorial notebook

  • Removed ‘Print’ from a verbose print message in _choose_mtx_rep

0.1.3 (07.12.2022)

  • Added supp_columns parameter to allow any column from liana to be returned.

  • Added return_all_lrs parameter to allow all interactions to be returned with a lrs_to_filter flag for the interaction that do not pass the expr_prop, and each of those interactions is assigned to the worst present score from the ones that do pass the threshold.

  • Fixed a bug where an exception was not thrown by assert_covered

  • Raise explicit exceptions as text in multiple places.

  • Changed cellphonedb p-values column name from “pvals” to “cellphone_pvals”.

0.1.2

  • Added CellChat and GeometricMean methods

0.1.1

  • Add progress bar to permutations

  • Deal with adata copies to optimize RAM

  • change copy to inplace, and assign to uns, rather than return adata

  • remove unnecessary filtering in _pre + extend units tests

0.1.0

  • Restructure API further

  • Submit to PIP

0.0.3

  • Added a filter according to min_cells per cell identity

  • prep_check_adata will now assert that groupby exists

  • extended test_pre.py tests

  • restructured the API to be more scverse-like

0.0.2

  • Added dotplot as a visualization option

  • Added basic_usage tutorial

0.0.1

First release alpha version of liana-py

  • Re-implementations of:

    • CellPhoneDB

    • NATMI

    • SingleCellSignalR

    • Connectome

    • logFC

    • Robust aggregate rank

  • Ligand-receptor resources as generated via OmniPathR.