hypergeom

topicpy.hypergeom.hypergeom

topicpy.hypergeom.parameters_for_hypergeometric(list_1: pandas.core.series.Series, list_2: pandas.core.series.Series) -> (<class 'float'>, <class 'float'>, <class 'float'>, <class 'float'>, (<class 'list'>, <class 'list'>))

Parameters:

• list_1 – series
• list_2 – series

lists of elements

Returns:

• x num of successes
• M population size
• k successes in population
• N sample size
• (list_1, list_2) tuple of original lists

Example:

l1 = pd.Series(index=[“ENSG00000000123”, “ENSG00000000456”, “ENSG00000000789”, “ENSG00000000XXX”], data=[“c1”, “c1”, “c1”, “c2”], dtype=str) l2 = pd.Series(index=[“ENSG00000000123”, “ENSG00000000456”, “ENSG00000000789”], data=[“c1”, “c1”, “c1”], dtype=str) x, M, k, N, _ = parameters_for_hypergeometric(l1, l2)

>>> x
    c1
c1   3
c2   0
>>> M
3
>>> k
{'c1': 3}
>>> N
{'c1': 3, 'c2': 1}

topicpy.hypergeom.build_map(num_successes, population_size, pop_successes, sample_sizes, lists, last_name=None)

topicpy.hypergeom.plot_map(df_cmap, first_name='topsbm', last_name='lda', *args, **kwargs)