Release notes

1.3.1

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

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.

Added conversion utility function translate_net to translate nets across organisms.

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.

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.