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Background

Population genomics is a field increasingly driven by statistical and computational methodologies. The shift towards computation, as new technologies have opened the door to very large data setsthat demand intensive computation, has revolutionized the field and added the “hats” of “statistician” and “programmer” to the heads of many evolutionary biologists. This kind of transformation is what happens in a progressive growing field of science, and is not, in itself, negative or problematic. The problem is that the growth and diversification of methodologies that are being developed to help investigators ask questions of the data is overwhelming for investigators. Increasingly the diversity of approaches and tools outstrips investigators’ ability to take advantage of them. The burden of this diversity of computational tools is not at all unique to population genomics, However this field has a high rate of introduction of new methods across the spectrum of summary statistic-based and model-based methodologies.