skbio.stats.composition.ANCOMBCResult#

class skbio.stats.composition.ANCOMBCResult(result, method, **kwargs)[source]#

Results for ANCOM-BC and ANCOM-BC2 analyses.

This class contains the primary differential abundance results. The object displays as the primary result table and supports [] selection like a pandas DataFrame. The underlying DataFrame is available through result. Post-hoc analyses are available as methods that compute on-demand when a grouping was specified in the upstream ancombc or ancombc2 call.

The primary result table has a (FeatureID, Covariate) multi-index. The index levels and columns are:

FeatureID: Feature identifier, i.e., dependent variable.
Covariate: Covariate name, i.e., independent variable.
Log(FC): Estimated model coefficient representing natural-log-fold change of abundance from the reference category to the covariate category defined in the formula. NaN indicates that the value is not estimable from the observed data.
SE: Standard error of the estimated coefficient, or NaN if not estimable.
W: W-statistic, calculated as the estimated coefficient value divided by its standard error.
pvalue: Uncorrected p-value of the W-statistic.
qvalue: p-value corrected for multiple testing.
Signif: Whether the covariate category is significantly differentially abundant from the reference category. A feature-covariate pair is marked as “True” if the q-value is less than or equal to the significance level.

See also

ancombc: ANCOM-BC function.
ancombc2: ANCOM-BC2 function.

Attributes

result

Primary differential abundance result table.

Methods

`dunnett_test`	Perform Dunnett's test (each group vs. reference) with mdFDR.
`global_test`	Perform global test for differential abundance across groups.
`pairwise_test`	Perform pairwise directional test between all group pairs.
`trend_test`	Perform trend test for ordered patterns in group effects.

Special methods

__getitem__

Select columns or rows from the primary result table.

Special methods (inherited)

`__eq__`	Return self==value.
`__ge__`	Return self>=value.
`__getstate__`	Helper for pickle.
`__gt__`	Return self>value.
`__hash__`	Return hash(self).
`__le__`	Return self<=value.
`__lt__`	Return self<value.
`__ne__`	Return self!=value.
`__str__`	Return str(self).

Details

result#: Primary differential abundance result table.

__getitem__(key)[source]#: Select columns or rows from the primary result table.