Predictive computational phenotyping and biomarker discovery using reference-free genome comparisons

Despite an era of supercomputing and increasingly precise instrumentation, many biological phenomena remain misunderstood. One approach to understanding such events is the elaboration of case-control studies, where a group of individuals that exhibit a given biological state (phenotype) is compared to a group of individuals that do not. In this setting, one seeks biological characteristics (biomarkers), that are predictive of the phenotype. Such biomarkers can serve as the basis for diagnostic tests, or they can guide the development of new therapies and drug treatments by providing insight on the biological processes that underlie a phenotype [1–4]. With the help of computational tools, such studies can be conducted at a much larger scale and produce more significant results.