proteometer.ptm_analysis
========================

.. py:module:: proteometer.ptm_analysis


Functions
---------

.. autoapisummary::

   proteometer.ptm_analysis.ptm_analysis
   proteometer.ptm_analysis.ptm_analysis_return_all


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

.. py:function:: ptm_analysis(par: proteometer.params.Params, drop_samples: list[str] | None = None) -> tuple[pandas.DataFrame, pandas.DataFrame]

   Runs the PTM proteomics processing and statistical analysis pipeline.

   This function reads in data from proteomics files specified in the `par`
   object, and performs normalization and batch correction, site-level rollup,
   and statistical analysis. The resulting DataFrame contains the processed PTM
   data, including the statistical results.

   :param par: A Params object that contains all the parameters for the analysis.
   :type par: Params
   :param drop_samples: A list of samples to be dropped from the analysis. Default is None.
   :type drop_samples: list[str], optional

   :returns:

             Two pandas DataFrames that contains the result of the PTM analysis.
                 The first is the processed PTM data, and the second is the global proteomics data.
   :rtype: tuple[pd.DataFrame,pd.DataFrame]


.. py:function:: ptm_analysis_return_all(par: proteometer.params.Params) -> tuple[pandas.DataFrame, pandas.DataFrame, pandas.DataFrame]

   Runs the PTM proteomics processing and statistical analysis pipeline.

   This function reads in data from proteomics files specified in the `par`
   object, and performs normalization and batch correction, site-level rollup,
   and statistical analysis. The resulting DataFrame contains the processed PTM
   data, including the statistical results.

   :param par: A Params object that contains all the parameters for the analysis.

   :returns:

             Three pandas DataFrames containing the results of the PTM analysis.
                 The first is the processed PTM data, which includes statistical results.
                 The second is the global proteomics data, normalized and batch-corrected.
                 The third is the uncorrected PTM data, which contains raw site-level data before normalization or correction.
   :rtype: tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]