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'.

Keywords

• multiple tests adjustment
• bonferroni
• p value
• open-source
• software
• statsmodels