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().