A new method for detecting significant p-values with applications to genetic data

A new method for detecting significant p-values is described in this paper. This method, based on the distribution of the m-th order statistic of a U(0; 1) distribution, is shown to be suitable in applications where m → ∞ independent hypothesis are tested and it is of interest for a fixed type I error probability to determine those being significant while controlling the false positives. Equivalencies and comparisons between our method and others methods based-on p-values are also established, and a graphical representation of the distribution of the test statistic is depicted for different values of m. Finally, our proposal is illustrated with two microarray data sets.