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Next-generation sequencing and other high-throughput technologies have made it feasible to characterize millions of sequence variations on large numbers of study participants. But when it comes to identifying a small number of these genetic features (or feature sets) that are associated with a disease trait, the investigator is faced with a formidable multiple-testing challenge. It can be thought of as a signal-to-noise problem, where the large number of unrelated genetic features tends to drown out the faint signal of the small number of biologically relevant features.

Screening-testing approaches for gene-gene and gene-environment interactions using independent statistics