train_integrated_ddpcr_model: Train integrated CASTLE model

In simondrue/castle: Fortify your ddPCR analyses for low-frequency variant detection

Description

Estimates the parameters of the statistical model for the integrated version the CASTLE algorithm based on a set of training samples, assumed to have no mutant DNA present.

Usage

train_integrated_ddpcr_model(background_samples, abc_grid_resolution = 25)

Arguments

background_samples	data.frame with cancer negative training samples as rows. These are the samples used to train/estimate the parameters of the model. At least the following columns should be present: WildtypeOnlyDroplets MutantOnlyDroplets DoubleNegativeDroplets DoublePositiveDroplets If data from QuataSoft is available, these can be imported using import_QS_files.
abc_grid_resolution	The resolution of the 3D-grid on which the integrated LR-test statistic is approximated. Default is 25 (equal to a grid of 25^3 = 15,625 points).

Details

In the test an integrated version of the Likelihood Ratio test statistic is used, and this is approximated using a Riemann sum on a 3D-grid. The parameter abc_grid_resolution controls this approximation as the sum is calculated on abc_grid_resolution^3 points. Higher values give better approximation but longer computation times.

Value

List of parameter estimates for the integrated CASLTE model. This should be used as input for test_tumor_sample_integrated.

See Also

import_QS_files, test_tumor_sample_integrated

simondrue/castle documentation built on Jan. 29, 2022, 3:04 a.m.