Unbiased distance correlation with sample-size-aware confidence bounds for comparative omics network analysis (opens in new tab)

IntroductionData-driven determination is a powerful approach for unbiased investigation of the functional relationships in biomolecular networks. Such networks can be inferred from omics data, where correlation analysis is a commonly used method. However, the correlation values depend strongly on sample variability and size of the sample set in the general case, leading to unstable results and possibly highly erroneous conclusions.MethodsIn this work, we show that similar to the Pearson and S...