senid.intrinsic

Functions

generate_loom_objects(adata, dataset_key, partition_key)	Generate loom files for each phenotype in the AnnData object.
prepare_files_for_inference(loom_directory, ...)
run_monod_inference(loom_directory, dataset_names, ...)
process_monod_fits(sr_arr, sd_arr, dir_string[, ...])
get_monod_de_genes(sr1, sr2, sd1, sd2, dname1, dname2, ...)

Package Contents

senid.intrinsic.generate_loom_objects(adata, dataset_key, partition_key, comparison_key=None, str_replace='-', output_directory='.', min_cells=100, return_groups=False, **kwargs)

Generate loom files for each phenotype in the AnnData object.

Parameters: - adata: AnnData object containing the data. - pheno_col: Column name in adata.obs that contains phenotype information. - data_directory: Directory to save the loom files.

Parameters:

• adata (anndata.AnnData)

• dataset_key (str)

• partition_key (str)

• comparison_key (str)

• str_replace (str)

• output_directory (str)

• min_cells (int)

• return_groups (bool)

senid.intrinsic.prepare_files_for_inference(loom_directory, dataset_names, transcriptome_filepath)

Parameters:

• loom_directory (str)

• dataset_names (list[str])

• transcriptome_filepath (str)

Return type:

Tuple[str, list[str]]

senid.intrinsic.run_monod_inference(loom_directory, dataset_names, transcriptome_filepath, dir_string, dataset_strings, phys_lb, phys_ub, samp_lb, samp_ub, gridsize, max_iterations=15, n_restarts=1, n_jobs=1)

Parameters:

• loom_directory (str)

• dataset_names (list[str])

• transcriptome_filepath (str)

• dir_string (str)

• dataset_strings (list[str])

• phys_lb (list[float])

• phys_ub (list[float])

• samp_lb (list[float])

• samp_ub (list[float])

• gridsize (list[int])

• max_iterations (int)

• n_restarts (int)

• n_jobs (int)

Return type:

None

senid.intrinsic.process_monod_fits(sr_arr, sd_arr, dir_string, plot_results=True, n_jobs=1)

Parameters:

• sr_arr (list[monod.inference.SearchResults])

• sd_arr (list[monod.extract_data.SearchData])

• dir_string (str)

• plot_results (bool)

• n_jobs (int)

Return type:

None

senid.intrinsic.get_monod_de_genes(sr1, sr2, sd1, sd2, dname1, dname2, gene_names, gf_rej=False, param_lfc=2.0, mean_lfc=1.0, pval_thr=0.05, outlier_de=True, single_nuc=False, correct_off=False)

Parameters:

• sr1 (monod.inference.SearchResults)

• sr2 (monod.inference.SearchResults)

• sd1 (monod.extract_data.SearchData)

• sd2 (monod.extract_data.SearchData)

• dname1 (str)

• dname2 (str)

• gene_names (list[str])

• gf_rej (bool)

• param_lfc (float)

• mean_lfc (float)

• pval_thr (float)

• outlier_de (bool)

• single_nuc (bool)

• correct_off (bool)

Return type:

pandas.DataFrame