LevelContextIOConfig

class pyprophet._config.LevelContextIOConfig(infile: str, outfile: str, subsample_ratio: float, level: str, context: str, context_fdr: ~typing.Literal['global', 'experiment-wide', 'run-specific'] = 'global', error_estimation_config: ~pyprophet._config.ErrorEstimationConfig = <factory>, color_palette: ~typing.Literal['normal', 'protan', 'deutran', 'tritan'] = 'normal', density_estimator: ~typing.Literal['kde', 'gmm'] = 'gmm', grid_size: int = 256)[source]

Bases: BaseIOConfig

Configuration for level-based context inference (e.g., peptide, protein, gene, glycopeptide) with FDR estimation and visualization options.

context_fdr

FDR estimation context scope: - “global”: Controls FDR across all runs and experiments. - “experiment-wide”: Controls FDR within the same experiment. - “run-specific”: Controls FDR independently for each run.

Type:: Literal[“global”, “experiment-wide”, “run-specific”]

error_estimation_config

Configuration for p-value and local FDR estimation. Includes options like: - Parametric vs non-parametric estimation - Pi₀ estimation method and smoothing - Local FDR transformations and truncation These are derived from –parametric, –pi0_method, –lfdr_transformation, etc.

Type:: ErrorEstimationConfig

color_palette

Color scheme to use in PDF reports or plots. Useful for accessibility. Options include normal vision and common types of color blindness.

Type:: Literal[“normal”, “protan”, “deutran”, “tritan”]

density_estimator

Only used for glycopeptide-level inference. Defines the method for score density estimation: - “kde”: Kernel Density Estimation. - “gmm”: Gaussian Mixture Model.

Type:: Literal[“kde”, “gmm”]

grid_size

Used in glycopeptide-level inference. Defines the number of grid cutoffs to build coordinates for local FDR calculation.

Type:: int

__eq__(other): Return self==value.

__hash__ = None

__init__(infile: str, outfile: str, subsample_ratio: float, level: str, context: str, context_fdr: ~typing.Literal['global', 'experiment-wide', 'run-specific'] = 'global', error_estimation_config: ~pyprophet._config.ErrorEstimationConfig = <factory>, color_palette: ~typing.Literal['normal', 'protan', 'deutran', 'tritan'] = 'normal', density_estimator: ~typing.Literal['kde', 'gmm'] = 'gmm', grid_size: int = 256) → None

__repr__(): Return repr(self).

classmethod from_cli_args(infile, outfile, subsample_ratio, level, context, context_fdr, parametric, pfdr, pi0_lambda, pi0_method, pi0_smooth_df, pi0_smooth_log_pi0, lfdr_truncate, lfdr_monotone, lfdr_transformation, lfdr_adj, lfdr_eps, color_palette, density_estimator, grid_size)[source]: Creates a configuration object from command-line arguments.