Biological Relevance Testing

Analyses of large-scale -omics datasets commonly use p-values as the indicators of statistical significance. However, considering p-value alone neglects the importance of effect size (i.e., the mean difference between groups) in determining the biological relevance of a significant difference. Here, we present a novel algorithm for computing a new statistic, the biological relevance testing (BRT) index, in the frequentist hypothesis testing framework to address this problem.


Reference manual

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1.1.0 by Le Zheng, 7 months ago

Browse source code at

Authors: Le Zheng[aut], Peng Yu[aut, cre]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports stats, ggplot2

See at CRAN