Release notes

1.6.X

Bug fixes

  • Fixed error in in get_contrast by reverting use of copy.deepcopy to copy.

  • Fixed verbose error regarding the number of unique sources being used in benchmark.

  • Added check for minimum version of igraph>=0.10.0 to properly render plot_network.

Changes

  • Resource functions such as get_resource or get_collectri now accept different genesymbol_resource than UniProt for gene translation to other organisms.

Additions

  • Added metric recall to the benchmark pipeline.

1.6.0

Bug fixes

  • Fixed wrong corrected p-values of get_metadata_associations whenever more than 10 factors were present.

  • Added static fallback for the most used omnipath resources, enabling their retrieval when internet connection is unstable.

  • Fixed ZeroDivisionError of gsea when many 0s were present.

  • dense_run now returns sorted features, which allows to run the benchmark pipeline ignoring zeros.

Changes

  • Methods now throw an error if there are repeated feature names in mat.

  • Functions can now accept AnnData objects with any sparse format than just scipy.sparse.csr_matrix.

  • get_pseudobulk now can return empty observations and features with the parameter remove_empty=False.

  • Fixed pandas warnings for categorical data across several functions.

  • plot_volcano and plot_volcano_df now can use different colors for positive, negative and null genes.

  • benchmark now has increased verbosity.

  • get_metadata_associations now has a verbose argument.

  • plot_associations now uses the marsilea plotting library instead of PyComplexHeatmap.

Additions

  • Added plot_network to visualize the network structure of top sources and their targets.

  • Added metrics rank and nrank to the benchmark pipeline.

  • Added dense argument to decouple to run methods ignoring zeroes per observation.

1.5.0

Bug fixes

  • run_mlm now uses the correct number of degrees of freedom to compute the t-value (one less than before), scores might change slightly.

  • rank_sources_groups now handles nan p-value results and skips whenever the group is equal to the reference.

  • get_pseudobulk now handles any sparse matrix format, can use individual lambda functions as mode and handles negative values when filtering for min_counts and min_cells.

  • Plotting functions with a grid now show it below dots instead of above.

Changes

  • All functions that deal with mat now do not enforce csr_matrix format automatically.

  • The benchmark pipeline now handles methods that provide only positive enrichment scores. Also added support for nan scores.

  • Modified get_ora_df to make it easier to use results of differential expression analysis, now returns different statistics.

  • gsea normalized score now is computed as in the original publication (ES+/mean(null+) and ES-/mean(null-)) instead of (ES - mean(null)) / sd(null).

  • run_ulm now runs faster.

  • get_collectri now returns the PMIDs supporting each interaction when available.

Additions

  • Added get_gsea_df function to run gsea directly on results of differential expression analysis, returns different statistics and the leading edge.

  • Added plot_dotplot function to plot results of get_ora_df.

  • Added plot_barplot_df function to plot results of get_ora_df.

  • Added plot_running_score function to plot results of get_gsea_df.

  • Added plot_associations function to check for significant covariates in the metadata.

1.4.0

Changes

  • get_pseudobulk changes:
    • Default values now do not filter features. For feature filtering check the new functions filter_by_expr or filter_by_prop.

    • If feature filters are used, it may return more genes than before due to a change of > min_props to >= min_props.

    • Now it returns quality control metrics such as psbulk_n_cells, psbulk_counts and psbulk_props.

    • Now groups_col accepts take multiple keys.

    • Now mode accepts a dictionary of callable functions. The resulting profiles will be stored in .layers.

  • swap_layer now has a new argument X_layer_key, a .layers key where to move and store the original .X.

  • Pseudobulk and bulk vignettes have been updated to use the PyDESeq2 package

  • run_consensus now accepts extra arguments with the new parametter args that are passed down to decouple.

  • Omnipath functions now return resources with sorted indexes and throw a warning if the version is too old.

  • run_wsum and run_wmean now correctly accept empty null distributions.

Additions

  • Added filter_by_expr feature filtering function from edgeR.

  • Added filter_by_prop feature filtering function. In previous versions it was incorporated inside get_pseudobulk.

  • Added plot_psbulk_samples to assess the quality of pseudobulk samples.

  • Added plot_filter_by_expr to assess which filtering thresholds to use in filter_by_expr.

  • Added plot_filter_by_prop to assess which filtering thresholds to use in filter_by_prop.

  • Added plot_volcano_df to plot volcano plots from long format dataframes.

  • Added plot_targets to plot downstream target genes of a source by their change and weight.

  • Added get_collectri to retrieve the CollecTRI gene regulatory network.

  • Added get_ksn_omnipath to retrieve the Kinase-Substrate network from omnipath.

  • Added rank_sources_groups to identify marker sources (TFs, pathways, etc.) per group of samples/cells.

1.3.4

Changes

  • get_pseudobulk now has new arguments: mode to change how to summarize profiles and skip_checks to bypass checks.

  • OmniPath functions now accept more organism synonyms.

Bug fixes

  • Fixed empty text labels bug for adjustText==0.8.

1.3.3

Bug fixes

  • read_gmt is now properly exported.

1.3.2

Bug fixes

  • plot_metrics_scatter_cols now deals with missing sources when comparing nets.

Changes

  • get_pseudobulk and get_acts now have a dtype argument due to future AnnData changes.

  • plot_metrics_scatter and plot_metrics_boxplot now use GroupBy.mean(numeric_only=True).

Additions

  • Added swap_layer function to easily move adata layers to .X.

  • Added read_gmt function to read GMT files containing gene sets.

1.3.1

Changes

  • Omnipath wrappers (get_resource, get_dorothea and get_progeny) now accept any organism name.

1.3.0

Bug fixes

  • Fixed change in api from sklearn.tree.

  • Forced gene names in extract to be in unicode format.

  • Changed integer format from int32 to int64 to accommodate larger datasets across methods.

Additions

  • Added conversion utility function translate_net to translate nets across organisms.

1.2.0

Bug fixes

  • Removed python <3.10 limitation.

  • Forced np.float32 type to output of get_contrast.

  • Made summarize_acts compatible with older versions of numpy.

  • extract_psbulk_inputs now checks if mat and obs have matching indexes.

  • plot_volcano now correctly can plot networks with different source names.

Changes

  • extract now removes empty samples and features.

  • run_consensus now follows the same format as other methods, old function is now called cons.

  • get_pseudobulk now checks if input are raw integer counts.

  • plot_volcano now can plot without subsetting features by a network and can save plots to disk.

  • plot_volcano now uses adjustText to better plot text labels.

  • plot_volcano now can set logFCs and p-value limits for outliers.

  • get_top_targets now can also work without subsetting features by a network and returns significant adjusted p-values.

  • get_contrast now can also work without needing to group.

  • udt and mdt now check if skranger and sklearn are installed, respectively.

  • get_toy_data now contains more example TFs.

  • get_top_targets now returns logFCs and pvals as column names instead of logFC and pval.

  • format_contrast_results now returns also the adjusted p-value.

Additions

  • Added dense_run util function which runs methods ignoring zeros in the data.

  • Added plot_violins and plot_barplot functions.

  • Added p_adjust_fdr util function to correct p-values for FDR.

  • Added get_ora_df function to infer ora from lists of genes instead of an input mat.

  • Added shuffle_net function to randomize networks.

  • Added benchmarking metrics metric_auroc, metric_auprc, metric_mcauroc and metric_mcauprc.

  • Added get_toy_benchmark_data function to generate a toy example for benchmarking.

  • Added show_metrics function to show available metrics.

  • Added benchmark, format_benchmark_inputs and get_performances functions to benchmark methods and nets.

  • Added plot_metrics_scatter function to plot the results of running the benchmarking pipeline.

  • Added plot_metrics_scatter_cols function to plot the results of running the benchmarking pipeline grouped by two levels.

  • Added plot_metrics_scatter function to plot the results of running the benchmarking pipeline.

  • Added plot_metrics_boxplot function to plot the distributions of Monte-Carlo benchmarking metrics.

1.1.0

Bug fixes

  • Fixed get_pseudobulk errors.

  • Fixed get_progeny to correctly return non duplicate entries.

  • Fixed run_viper parallelization error.

  • Fixed run_ora to correctly deal with random ties.

Changes

  • get_dorothea now returns an ordered dataframe.

  • get_contrast now prints warnings instead of returning an empty dataframe.

Additions

  • Added get_top_targets util function.

  • Added format_contrast_results util function.