In silico approaches for next generation sequencing (NGS) data modeling have utility in the clinical laboratory as a tool for clinical assay validation. In silico NGS data can take a variety of forms including pure simulated data or manipulated data files in which variants are inserted into existing data files. In silico data allow for simulation of a range of variants that may be difficult to obtain from a single physical sample. Such data allows laboratories to more accurately test the performance of bioinformatics analysis pipelines without sequencing additional cases. For example, libraries may use in silico data to simulate low variant allele frequency mutations to test the sensitivity of variant calling software or simulate a range of insertion/deletion sizes to determine the performance of indel calling software. In this manuscript, we review the different types of in silico data, how in silico data is created, and how it can be used in the clinical laboratory. We present survey data from the AMP membership indicating how in silico NGS data is currently being used. Finally, we present potential use cases in which in silico data may become useful in the future.