title: EDISON-WMW: Exact Dynamic Programing Solution of the Wilcoxon-Mann-Whitney Test.
abstract: In many research disciplines, hypothesis tests are applied to evaluate whether findings are statistically significant or could be explained by chance. The Wilcoxon-Mann-Whitney (WMW) test is among the most popular hypothesis tests in medicine and life science to analyze if two groups of samples are equally distributed. This nonparametric statistical homogeneity test is commonly applied in molecular diagnosis. Generally, the solution of the WMW test takes a high combinatorial effort for large sample cohorts containing a significant number of ties. Hence, P value is frequently approximated by a normal distribution. We developed EDISON-WMW, a new approach to calculate the exact permutation of the two-tailed unpaired WMW test without any corrections required and allowing for ties. The method relies on dynamic programing to solve the combinatorial problem of the WMW test efficiently. Beyond a straightforward implementation of the algorithm, we presented different optimization strategies and developed a parallel solution. Using our program, the exact P value for large cohorts containing more than 1000 samples with ties can be calculated within minutes. We demonstrate the performance of this novel approach on randomly-generated data, benchmark it against 13 other commonly-applied approaches and moreover evaluate molecular biomarkers for lung carcinoma and chronic obstructive pulmonary disease (COPD). We found that approximated P values were generally higher than the exact solution provided by EDISON-WMW. Importantly, the algorithm can also be applied to high-throughput omics datasets, where hundreds or thousands of features are included. To provide easy access to the multi-threaded version of EDISON-WMW, a web-based solution of our algorithm is freely available at http://www.ccb.uni-saarland.de/software/wtest/.
authors.affiliation: Chair for Clinical Bioinformatics, Medical Faculty, Saarland University, Saarbrücken 66123, Germany.
authors.forename: Alexander
authors.initials: A
authors.lastname: Marx
authors.affiliation: Chair for Clinical Bioinformatics, Medical Faculty, Saarland University, Saarbrücken 66123, Germany.
authors.forename: Christina
authors.initials: C
authors.lastname: Backes
authors.affiliation: Department of Human Genetics, Saarland University, University Hospital, Homburg 66421, Germany.
authors.forename: Eckart
authors.initials: E
authors.lastname: Meese
authors.affiliation: Chair for Bioinformatics, Saarland University, Saarbrücken 66123, Germany.
authors.forename: Hans-Peter
authors.initials: HP
authors.lastname: Lenhof
authors.affiliation: Chair for Clinical Bioinformatics, Medical Faculty, Saarland University, Saarbrücken 66123, Germany. Electronic address: andreas.keller@ccb.uni-saarland.de.
authors.forename: Andreas
authors.initials: A
authors.lastname: Keller
mesh_terms: D000465:Algorithms; D015415:Biomarkers / Q000378:metabolism; D016022:Case-Control Studies; D006801:Humans; D008175:Lung Neoplasms / Q000235:genetics / Q000473:pathology; D035683:MicroRNAs / Q000378:metabolism; D029424:Pulmonary Disease, Chronic Obstructive / Q000235:genetics / Q000473:pathology; D060888:Real-Time Polymerase Chain Reaction
chemical_list: D015415:Biomarkers; D035683:MicroRNAs
keywords: Dynamic programing; Exact permutation; Parallel optimization; Wilcoxon rank-sum test; Wilcoxon–Mann–Whitney test
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