Variance modeling¶
In order to obtain measures of statistical significance for 5C interactions, we
need a quantitative measure of statistical noise for each interaction. lib5c
provides a variety of methods for estimating this variance.
Command-line interfaces¶
To model the variance, run
$ lib5c variance
To visualize variance estimates, run
$ lib5c plot visualize-variance
Exposed functionality¶
The subpackage responsible for variance modeling is
lib5c.algorithms.variance
.
The top-level convenience function exposed is
lib5c.algorithms.variance.estimate_variance()
estimate_variance()
provides easy access to all available variance
estimation methods.
For an example of how to visualize variance estimates using
lib5c.plotters.scatter.scatter()
or
lib5c.plotters.curve_fits.plot_fit()
, take a look at
lib5c.tools.visualize_variance.visualize_variance_tool()
.