statistics_report

class pyprophet.levels_contexts.statistics_report(data, parametric, pfdr, pi0_lambda, pi0_method, pi0_smooth_df, pi0_smooth_log_pi0, lfdr_truncate, lfdr_monotone, lfdr_transformation, lfdr_adj, lfdr_eps, writer)[source]

Bases:

Generates error statistics and updates the input data with FDR-related metrics.

Parameters:

  • data (pd.DataFrame) – Input data containing scores and decoy labels.

  • parametric (bool) – Whether to use parametric FDR estimation.

  • pfdr (bool) – Whether to use pFDR estimation.

  • pi0_lambda (list) – Lambda values for pi0 estimation.

  • pi0_method (str) – Method for pi0 estimation.

  • pi0_smooth_df (int) – Degrees of freedom for pi0 smoothing.

  • pi0_smooth_log_pi0 (bool) – Whether to log-transform pi0 values.

  • lfdr_truncate (bool) – Whether to truncate local FDR values.

  • lfdr_monotone (bool) – Whether to enforce monotonicity in local FDR values.

  • lfdr_transformation (str) – Transformation method for local FDR.

  • lfdr_adj (float) – Adjustment factor for local FDR.

  • lfdr_eps (float) – Epsilon value for local FDR.

  • writer (Writer) – Writer object for saving reports.

Returns:

Updated data with FDR-related metrics.

Return type:

pd.DataFrame