Rank product

In addition to its use in expression profiling, it can be used to combine ranked lists in various application domains, including proteomics, metabolomics, statistical meta-analysis, and general feature selection.

Compute the rank product via the geometric mean: Simple permutation-based estimation is used to determine how likely a given RP value or better is observed in a random experiment.

Calculation of the exact p-values offers a substantial improvement over permutation approximation, most significantly for that part of the distribution rank product analysis is most interested in, i.e., the thin right tail.

However, exact statistical significance of large rank products may take unacceptable long amounts of time to compute.

Heskes, Eisinga and Breitling (2014) provide a method to determine accurate approximate p-values of the rank product statistic in a computationally fast manner.

Filled circles represent ranks of one gene in the different replicates. The rank product for this gene would be (2×1×4×2) 1/4 = 2