Abstract: Described herein are methods of assessing a sample-specific performance of a copy number variant model, a method for determining a copy number of an interrogated segment within a region of interest, and a method for determining a copy number variant abnormality within a region of interest. Sample-specific performance of the copy number variant caller is assessed by parameterizing a copy number variant model base on sequencing reads from a test sample, generating synthetic copy number variants using the sequencing read from the test sample, and calling the number of copies in the synthetic copy number variants using the copy number variant model and the sample-specific parameters. Calling a number of copies of an interrogated segment can include parameterizing a hidden Markov model using an analytic first derivative gradient and second derivative Hessian of one or more parameters in a copy number likelihood model.

Abstract: A computer-implemented method for optimizing performance of a DNA-based noninvasive prenatal screen includes generating a plurality of synthetic sequencing datasets by, for each of the plurality of synthetic sequencing datasets, (i) generating at least one of a plurality of synthetic copy number variants comprising a synthetic number of copies of at least a portion of a region of interest represented by a synthetic number of sequencing reads from one or more segments within the region of interest, and (ii) modifying a real sequencing dataset, which includes genetic sequencing data from a real test sample comprising maternal and fetal cfDNA, by replacing a number of real sequencing reads from the one or more segments within the region of interest in the real test sample with the synthetic number of sequencing reads. Various other methods and systems are also disclosed.