proteometer.normalization
=========================

.. py:module:: proteometer.normalization


Functions
---------

.. autoapisummary::

   proteometer.normalization.peptide_normalization
   proteometer.normalization.peptide_batch_correction
   proteometer.normalization.peptide_normalization_and_correction
   proteometer.normalization.tmt_normalization
   proteometer.normalization.median_normalize_columns
   proteometer.normalization.median_normalization
   proteometer.normalization.batch_correction


Module Contents
---------------

.. py:function:: peptide_normalization(global_pept: pandas.DataFrame, mod_pept: pandas.DataFrame, int_cols: list[str], par: proteometer.params.Params) -> pandas.DataFrame

   Normalizes and applies batch correction to peptide data.

   :param global_pept: Global peptide data.
   :type global_pept: pd.DataFrame
   :param mod_pept: Modified peptide data.
   :type mod_pept: pd.DataFrame
   :param int_cols: List of intensity column names.
   :type int_cols: list[str]
   :param metadata: Metadata for batch correction.
   :type metadata: pd.DataFrame
   :param par: Parameters object containing experiment settings.
   :type par: Params

   :returns: Normalized and batch-corrected peptide data.
   :rtype: pd.DataFrame


.. py:function:: peptide_batch_correction(mod_pept: pandas.DataFrame, metadata: pandas.DataFrame, par: proteometer.params.Params) -> pandas.DataFrame

   Normalizes and applies batch correction to peptide data.

   :param global_pept: Global peptide data.
   :type global_pept: pd.DataFrame
   :param mod_pept: Modified peptide data.
   :type mod_pept: pd.DataFrame
   :param int_cols: List of intensity column names.
   :type int_cols: list[str]
   :param metadata: Metadata for batch correction.
   :type metadata: pd.DataFrame
   :param par: Parameters object containing experiment settings.
   :type par: Params

   :returns: Normalized and batch-corrected peptide data.
   :rtype: pd.DataFrame


.. py:function:: 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

   Normalizes and applies batch correction to peptide data.

   :param global_pept: Global peptide data.
   :type global_pept: pd.DataFrame
   :param mod_pept: Modified peptide data.
   :type mod_pept: pd.DataFrame
   :param int_cols: List of intensity column names.
   :type int_cols: list[str]
   :param metadata: Metadata for batch correction.
   :type metadata: pd.DataFrame
   :param par: Parameters object containing experiment settings.
   :type par: Params

   :returns: Normalized and batch-corrected peptide data.
   :rtype: pd.DataFrame


.. py:function:: tmt_normalization(df2transform: pandas.DataFrame, global_pept: pandas.DataFrame, int_cols: list[str]) -> pandas.DataFrame

   Performs TMT normalization on peptide data.

   :param df2transform: DataFrame to transform.
   :type df2transform: pd.DataFrame
   :param global_pept: Global peptide data for reference.
   :type global_pept: pd.DataFrame
   :param int_cols: List of intensity column names.
   :type int_cols: list[str]

   :returns: TMT-normalized DataFrame.
   :rtype: pd.DataFrame


.. py:function:: median_normalize_columns(df: pandas.DataFrame, cols: list[str], skipna: bool = True, zero_center: bool = False) -> pandas.DataFrame

   Performs median normalization on columns of a DataFrame.

   :param df: DataFrame to transform.
   :type df: pd.DataFrame
   :param cols: List of column names to normalize.
   :type cols: list[str]
   :param skipna: Whether to skip NaN values. Defaults to True.
   :type skipna: bool, optional
   :param zero_center: Whether to zero-center the data. Defaults to False.
   :type zero_center: bool, optional

   :returns: Median-normalized DataFrame.
   :rtype: pd.DataFrame


.. py:function:: 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

   Performs median normalization on peptide data.

   :param df: DataFrame to transform.
   :type df: pd.DataFrame
   :param int_cols: List of intensity column names.
   :type int_cols: list[str]
   :param metadata_ori: Metadata for batch correction. Defaults to None.
   :type metadata_ori: pd.DataFrame | None, optional
   :param batch_correct_samples: Samples to correct. Defaults to None.
   :type batch_correct_samples: Iterable[str] | pd.Series[str] | None, optional
   :param batch_col: Batch column name. Defaults to None.
   :type batch_col: str | None, optional
   :param sample_col: Sample column name. Defaults to "Sample".
   :type sample_col: str, optional
   :param skipna: Whether to skip NaN values. Defaults to True.
   :type skipna: bool, optional
   :param zero_center: Whether to zero-center the data. Defaults to False.
   :type zero_center: bool, optional

   :returns: Median-normalized DataFrame.
   :rtype: pd.DataFrame


.. py:function:: 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

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

   :param df4batcor: DataFrame to correct.
   :type df4batcor: pd.DataFrame
   :param metadata: Metadata for batch correction.
   :type metadata: pd.DataFrame
   :param batch_correct_samples: Samples (column names) to correct. Defaults to None, in which case it is all samples as defined in metadata.
   :type batch_correct_samples: Iterable[str] | pd.Series[str] | None, optional
   :param batch_col: Batch column name. Defaults to "Batch".
   :type batch_col: str, optional
   :param sample_col: Sample column name. Defaults to "Sample".
   :type sample_col: str, optional

   :returns: Batch-corrected DataFrame.
   :rtype: pd.DataFrame