alphabase.scoring.fdr#

Functions:

calc_fdr_for_df(df, score_column[, decoy_column])

Calculate FDR values (q_values in fact) for the given dataframe

calc_fdr_from_ref_for_df(df, ref_scores, ...)

Calculate FDR values for a PSM dataframe from the given reference

calculate_fdr(df, score_column[, decoy_column])

Calculate FDR values (q_values in fact) for the given dataframe

calculate_fdr_from_ref(df, ref_scores, ...)

Calculate FDR values for a PSM dataframe from the given reference

fdr_from_ref(sorted_scores, ref_scores, ...)

Calculate FDR values from the given reference scores and fdr_values.

fdr_to_q_values(fdr_values)

convert FDR values to q_values.
alphabase.scoring.fdr.calc_fdr_for_df(df: DataFrame, score_column: str, decoy_column: str = 'decoy') → DataFrame[source]#

Calculate FDR values (q_values in fact) for the given dataframe

Parameters:

  • df (pd.DataFrame) – PSM dataframe to calculate FDRs

  • score_column (str) – score column to sort in decending order

  • decoy_column (str, optional) – decoy column in the dataframe. 1=target, 0=decoy. Defaults to ‘decoy’.

Returns:

PSM dataframe with ‘fdr’ column added

Return type:

pd.DataFrame

alphabase.scoring.fdr.calc_fdr_from_ref_for_df(df: DataFrame, ref_scores: ndarray, ref_fdr_values: ndarray, score_column: str, decoy_column: str = 'decoy') → DataFrame[source]#
Calculate FDR values for a PSM dataframe from the given reference

scores and fdr_values. It is used to extend peptide-level or sequence-level FDR (reference) to each PSM, as PSMs are more useful for quantification.

``

Parameters:

  • df (pd.DataFrame) – PSM dataframe

  • ref_scores (np.array) – reference scores that used to calculate ref_fdr_values, also sorted in decending order.

  • ref_fdr_values (np.array) – fdr values corresponding to ref_scores

  • score_column (str) – score column in the dataframe

  • decoy_column (str, optional) – decoy column in the dataframe. 1=target, 0=decoy. Defaults to ‘decoy’.

Returns:

dataframe with ‘fdr’ column added

Return type:

pd.DataFrame

alphabase.scoring.fdr.calculate_fdr(df: DataFrame, score_column: str, decoy_column: str = 'decoy') → DataFrame[source][source]#

Calculate FDR values (q_values in fact) for the given dataframe

Parameters:

  • df (pd.DataFrame) – PSM dataframe to calculate FDRs

  • score_column (str) – score column to sort in decending order

  • decoy_column (str, optional) – decoy column in the dataframe. 1=target, 0=decoy. Defaults to ‘decoy’.

Returns:

PSM dataframe with ‘fdr’ column added

Return type:

pd.DataFrame

alphabase.scoring.fdr.calculate_fdr_from_ref(df: DataFrame, ref_scores: ndarray, ref_fdr_values: ndarray, score_column: str, decoy_column: str = 'decoy') → DataFrame[source][source]#
Calculate FDR values for a PSM dataframe from the given reference

scores and fdr_values. It is used to extend peptide-level or sequence-level FDR (reference) to each PSM, as PSMs are more useful for quantification.

``

Parameters:

  • df (pd.DataFrame) – PSM dataframe

  • ref_scores (np.array) – reference scores that used to calculate ref_fdr_values, also sorted in decending order.

  • ref_fdr_values (np.array) – fdr values corresponding to ref_scores

  • score_column (str) – score column in the dataframe

  • decoy_column (str, optional) – decoy column in the dataframe. 1=target, 0=decoy. Defaults to ‘decoy’.

Returns:

dataframe with ‘fdr’ column added

Return type:

pd.DataFrame

alphabase.scoring.fdr.fdr_from_ref(sorted_scores: ndarray, ref_scores: ndarray, ref_fdr_values: ndarray) → ndarray[source]#

Calculate FDR values from the given reference scores and fdr_values. It is used to extend peptide-level or sequence-level FDR (reference) to each PSM, as PSMs are more useful for quantification.

Parameters:

  • sorted_scores (np.array) – the scores to calculate FDRs, they must be sorted in decending order.

  • ref_scores (np.array) – reference scores that used to calculate ref_fdr_values, also sorted in decending order.

  • ref_fdr_values (np.array) – fdr values corresponding to ref_scores

Returns:

fdr values corresponding to sorted_scores.

Return type:

np.array

alphabase.scoring.fdr.fdr_to_q_values(fdr_values: ndarray) → ndarray[source]#

convert FDR values to q_values.

Parameters:

fdr_values (np.ndarray) – FDR values, they should be sorted according to the descending order of the score

Returns:

q_values

Return type:

np.ndarray