Combining P-values from multiple statistical tests is a common exercise in bioinformatics. However, this procedure is non-trivial for dependent P-values. Here, we discuss an empirical adaptation of Browns method (an extension of Fishers method) for combining dependent P-values which is appropriate for the large and correlated datasets found in high-throughput biology.