proteometer.normalization#

Functions#

peptide_normalization(→ pandas.DataFrame)

Normalizes and applies batch correction to peptide data.

peptide_batch_correction(→ pandas.DataFrame)

Normalizes and applies batch correction to peptide data.

peptide_normalization_and_correction(→ pandas.DataFrame)

Normalizes and applies batch correction to peptide data.

tmt_normalization(→ pandas.DataFrame)

Performs TMT normalization on peptide data.

median_normalize_columns(→ pandas.DataFrame)

Performs median normalization on columns of a DataFrame.

median_normalization(→ pandas.DataFrame)

Performs median normalization on peptide data.

batch_correction(→ pandas.DataFrame)

Applies batch correction to peptide data using row-mean centering.

Module Contents#

proteometer.normalization.peptide_normalization(global_pept: pandas.DataFrame, mod_pept: pandas.DataFrame, int_cols: list[str], par: proteometer.params.Params) → pandas.DataFrame[source]#

Normalizes and applies batch correction to peptide data.

Parameters:

  • global_pept (pd.DataFrame) – Global peptide data.

  • mod_pept (pd.DataFrame) – Modified peptide data.

  • int_cols (list[str]) – List of intensity column names.

  • metadata (pd.DataFrame) – Metadata for batch correction.

  • par (Params) – Parameters object containing experiment settings.

Returns:

Normalized and batch-corrected peptide data.

Return type:

pd.DataFrame

proteometer.normalization.peptide_batch_correction(mod_pept: pandas.DataFrame, metadata: pandas.DataFrame, par: proteometer.params.Params) → pandas.DataFrame[source]#

Normalizes and applies batch correction to peptide data.

Parameters:

  • global_pept (pd.DataFrame) – Global peptide data.

  • mod_pept (pd.DataFrame) – Modified peptide data.

  • int_cols (list[str]) – List of intensity column names.

  • metadata (pd.DataFrame) – Metadata for batch correction.

  • par (Params) – Parameters object containing experiment settings.

Returns:

Normalized and batch-corrected peptide data.

Return type:

pd.DataFrame

proteometer.normalization.peptide_normalization_and_correction(global_pept: pandas.DataFrame, mod_pept: pandas.DataFrame, int_cols: list[str], metadata: pandas.DataFrame, par: proteometer.params.Params) → pandas.DataFrame[source]#

Normalizes and applies batch correction to peptide data.

Parameters:

  • global_pept (pd.DataFrame) – Global peptide data.

  • mod_pept (pd.DataFrame) – Modified peptide data.

  • int_cols (list[str]) – List of intensity column names.

  • metadata (pd.DataFrame) – Metadata for batch correction.

  • par (Params) – Parameters object containing experiment settings.

Returns:

Normalized and batch-corrected peptide data.

Return type:

pd.DataFrame

proteometer.normalization.tmt_normalization(df2transform: pandas.DataFrame, global_pept: pandas.DataFrame, int_cols: list[str]) → pandas.DataFrame[source]#

Performs TMT normalization on peptide data.

Parameters:

  • df2transform (pd.DataFrame) – DataFrame to transform.

  • global_pept (pd.DataFrame) – Global peptide data for reference.

  • int_cols (list[str]) – List of intensity column names.

Returns:

TMT-normalized DataFrame.

Return type:

pd.DataFrame

proteometer.normalization.median_normalize_columns(df: pandas.DataFrame, cols: list[str], skipna: bool = True, zero_center: bool = False) → pandas.DataFrame[source]#

Performs median normalization on columns of a DataFrame.

Parameters:

  • df (pd.DataFrame) – DataFrame to transform.

  • cols (list[str]) – List of column names to normalize.

  • skipna (bool, optional) – Whether to skip NaN values. Defaults to True.

  • zero_center (bool, optional) – Whether to zero-center the data. Defaults to False.

Returns:

Median-normalized DataFrame.

Return type:

pd.DataFrame

proteometer.normalization.median_normalization(df: pandas.DataFrame, int_cols: list[str], metadata: pandas.DataFrame | None = None, batch_correct_samples: collections.abc.Iterable[str] | pandas.Series[str] | None = None, batch_col: str | None = None, sample_col: str = 'Sample', skipna: bool = True, zero_center: bool = False) → pandas.DataFrame[source]#

Performs median normalization on peptide data.

Parameters:

  • df (pd.DataFrame) – DataFrame to transform.

  • int_cols (list[str]) – List of intensity column names.

  • metadata_ori (pd.DataFrame | None, optional) – Metadata for batch correction. Defaults to None.

  • batch_correct_samples (Iterable[str] | pd.Series[str] | None, optional) – Samples to correct. Defaults to None.

  • batch_col (str | None, optional) – Batch column name. Defaults to None.

  • sample_col (str, optional) – Sample column name. Defaults to “Sample”.

  • skipna (bool, optional) – Whether to skip NaN values. Defaults to True.

  • zero_center (bool, optional) – Whether to zero-center the data. Defaults to False.

Returns:

Median-normalized DataFrame.

Return type:

pd.DataFrame

proteometer.normalization.batch_correction(df4batcor: pandas.DataFrame, metadata: pandas.DataFrame, batch_correct_samples: collections.abc.Iterable[str] | pandas.Series[str] | None = None, batch_col: str = 'Batch', sample_col: str = 'Sample') → pandas.DataFrame[source]#

Applies batch correction to peptide data using row-mean centering.

Parameters:

  • df4batcor (pd.DataFrame) – DataFrame to correct.

  • metadata (pd.DataFrame) – Metadata for batch correction.

  • batch_correct_samples (Iterable[str] | pd.Series[str] | None, optional) – Samples (column names) to correct. Defaults to None, in which case it is all samples as defined in metadata.

  • batch_col (str, optional) – Batch column name. Defaults to “Batch”.

  • sample_col (str, optional) – Sample column name. Defaults to “Sample”.

Returns:

Batch-corrected DataFrame.

Return type:

pd.DataFrame