Standards for reproducible science build a foundation of trust in the body of literature that informs the next experimental studies researchers conduct. However, the increasing complexity and scale of data and discoveries across scientific fields including genomics has exacerbated the burden of maintaining reproducibility standards. With the advent of next generation sequencing, many innovations in assay development have especially contributed to the complexity and scale within this subfield. This has created an increased demand for tools that perform quality checks and flexible analysis of genomics data that are compatible with a variety of genomic assays. To perform post-sequencing quality controls of genetic backgrounds, we developed the Genotype validation Pipeline (GenoPipe) to detect insertion and deletion modifications along with variant-based strain backgrounds. We identify samples from publicly available data to demonstrate the value of performing this quality control step on genomic data. Subsequent analysis workflows can be built using ScriptManager, a flexible tool that performs modular operations on genomic data to build customized workflows during tracked interactive sessions using an accessible graphical interface. When it comes time to publish, researchers can model their submissions off our recommended file template to intuitively organize their work for readers. This template describes the files structure and incorporates the use of both GenoPipe and ScriptManager into its ordinal execution to enhance the scalability, reproducibility, and flexibility of workflows. To date, the template has been applied and customized for multiple publications to enhance the comparability of future results. Together, these tools support the start to finish analysis of a reproducible research project.