:py:mod:`micom.stats`
=====================

.. py:module:: micom.stats

.. autoapi-nested-parse::

   Data warngling and statistics for MICOM.



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


Functions
~~~~~~~~~

.. autoapisummary::

   micom.stats.fdr_adjust
   micom.stats._run_test
   micom.stats._run_corr
   micom.stats.compare_groups
   micom.stats.correlate_fluxes



.. py:function:: fdr_adjust(p)

   Get FDR cutoffs for p-values with Benjamini-Hochberg.

   :param p: The original p-values. Can not contain naNs.
   :type p: list[float]

   :returns: * *A numpy array of FDR cutoffs (q-values). This is commonly known as "adjusted"*
             * *p-values.*


.. py:function:: _run_test(args)


.. py:function:: _run_corr(args)


.. py:function:: compare_groups(fluxes, metadata_column, groups=None, threads=1, progress=True)

   Compare fluxes form different sample groups.

   .. note::

      This uses a non-parametric test by default. By default it will use a
      Mann-Whitney test for two groups and a Kruskal-Wallis test for >2 groups.
      `q` are the FDR-corrected p-values (Benjamini-Hochberg correction).

   :param fluxes: A frame with net fluxes as returned by `production_rates` or
                  `consumption_rates`.
   :type fluxes: pandas.DataFrame
   :param metatdata_column: The column of the DataFrame denoting the groups.
   :type metatdata_column: str
   :param groups: Specify a subset of groups you want to compare or define the order (1st will
                  be the reference group). If None will use the groups as they appear in
                  the DataFrame.
   :type groups: list[str] or None
   :param threads: How many threads to use to run tests in parallel.
   :type threads: int
   :param progress: Whether to show a progress bar.
   :type progress: bool

   :rtype: Returns the metabolite with their respective test statistics.


.. py:function:: correlate_fluxes(fluxes, metadata_column, threads=1, progress=True)

   Correlate fluxes with a continuous covariate.

   .. note::

      This uses a non-parametric test by default (Spearman rank correlation). `q`
      are the FDR-corrected p-values (Benjamini-Hochberg correction).

   :param fluxes: A frame with net fluxes as returned by `production_rates` or
                  `consumption_rates`.
   :type fluxes: pandas.DataFrame
   :param metatdata_column: The column of the DataFrame denoting the covariate.
   :type metatdata_column: str
   :param threads: How many threads to use to run tests in parallel.
   :type threads: int
   :param progress: Whether to show a progress bar.
   :type progress: bool

   :rtype: Returns the metabolite with their respective test statistics.