Testing a hypothesis – non-stationary or time-reversible

We test the hypothesis that the GTR model is sufficient for a data set, compared with the GN (non-stationary general nucleotide model).

result is a hypothesis_result object. The repr() displays the likelihood ratio test statistic, degrees of freedom and associated p-value>

In this case, we accept the null given the p-value is > 0.05. We use this object to demonstrate the properties of a hypothesis_result.

hypothesis_result has attributes and keys

Accessing the test statistics

The null hypothesis

This model is accessed via the null attribute.

The alternate hypothesis

Saving hypothesis results

You are advised to save these results as serialised data since this provides maximum flexibility for downstream analyses.

The following would write the result into a sqlitedb.

from cogent3 import get_app, open_data_store

output = open_data_store("path/to/myresults.sqlitedb", mode="w")
writer = get_app("write_db", data_store=output)
writer(result)