Establishing mathematical laws of genomic variation

As the biological arm of the Rasch community, genomic measurement is concerned with asserting and testing hypotheses regarding the quantitative status of genomic variables, including alleles, genotypes, gene expression levels, and phenotypes, as well as DNA, RNA, and protein sequence information. The defining goal of this scientific paradigm, in contrast to the sample-dependent model-fitting and deterministic hypothesis testing of classical statistical genetics, is the identification, validation, and maintenance of a common unit of genomic measurement that maintains its magnitude and meaning, within an allowable range of error, regardless of the laboratory technology used to generate outcomes or the particular group of individuals or organisms under investigation. Such an invariant metric, the basis of a standard genometric scale and associated system of genomic metrology, can be identified, validated, and maintained through 1) routine implementation of the Rasch family of measurement models to construct sample- and scale-free measures from different types of genomic data and 2) cross-calibration of genomic measurement instruments between and among researchers, laboratories, universities, corporations, and databases. This manuscript provides an introductory overview of the guiding principles of fundamental measurement theory and the work of Rasch, connects these concepts to well-known tenets of population genetics, and highlights the potential benefits, both theoretical and applied, associated with achieving objectivity in genomic measurement.