
Open-Source MUltiple Tests Corrections and FOrmatted Tables Software (MUFOS)
Abstract
The p value statistic remains a ubiquitous indicator of the verisimilitude of experimental hypotheses. However, testing multiple hypotheses poses a problem as Type I error rate is inflated. Despite known solutions, this problem remains largely neglected for two reasons: 1) most data analysis tools offer limited multiple tests correction options; 2) the learning curve of existing tools requires hefty time investment. To address these concerns, we present a free, easy-to-use and convenient Software, built around established python libraries, that allows users to apply a MUltiple tests correction and get the results in a readily-understood, FOrmatted table (MUFOS) – https://github.com/nikbpetrov/mufos.
© 2022 Nikolay Petrov, Vasil Atanasov, Trevor Thompson, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.