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Most contemporary genomic studies are highly driven by bioinformatic methods and tools. Are there still problems that require classical statistical thinking and solutions? I discuss several foundational statistical issues that are important for design, conduct, and interpretation of genomic studies. These include preferred properties of test statistics, standards for statistical significance, and predictive modeling vs. basic science.
