Separate Class True Discovery Rate Degree of Association Sets for Biomarker Identification

What is it about?

Efron's separate class approach can increase the power of discovery analyses controlling the false discovery rate (FDR). This paper applies the separate class approach to TDRDA analyses, the goal of which is to identify biomarkers with strong association (not just any association) with an endpoint

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Why is it important?

Discovery analyses can have low power if very few of the features analyzed have strong association with outcome. If pre-specified classes of features are enriched for truly predictive features, the identification power (probability of identifying features while controlling FDR) increases.