Robust Computational Approaches to Defining Insights on the Interface of DNA Repair with Replication and Transcription in Cancer

The massive amount of experimental DNA and RNA sequence information provides an encyclopedia for cell biology that requires computational tools for efficient interpretation. The ability to write and apply simple computing scripts propels the investigator beyond the boundaries of online analysis tools to more broadly interrogate laboratory experimental data and to integrate them with all available datasets to test and challenge hypotheses. Here we describe robust prototypic bash and C++ scripts with metrics and methods for validation that we have made publicly available to address the roles of non-B DNA-forming motifs in eliciting genetic instability and to query The Cancer Genome Atlas. Importantly, the methods presented provide practical data interpretation tools to examine fundamental relationships and to enable insights and correlations between alterations in gene expression patterns and patient outcome. The exemplary source codes described are simple and can be efficiently modified, elaborated, and applied to other relationships and areas of investigation.