Beware of counter-intuitive levels of false discoveries in datasets with strong intra-correlations
Chakravarthi Kanduri, Maria Mamica, Emilie Willoch Olstad, Manuela Zucknick, Jingyi Jessica Li, Geir Kjetil Sandve · Genome biology · 2025
The false discovery rate (FDR) controlling method by Benjamini and Hochberg (BH) is a popular choice in the omics fields. Here, we demonstrate that in datasets with a large degree of dependencies between features, FDR correction methods like BH can sometimes counter-intuitively report very high numbers of false positives, potentially misleading researchers. We call the attention of researchers to use suited multiple testing strategies and approaches like synthetic null data (negative control) to identify and minimize caveats related to false discoveries, as in the cases where false findings do occur, they may be numerous.