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Due to the advance in technology, the type of data is getting more complicated and large-scale. To analyze such complex data, more advanced technique is required. In case of omics data from two different groups, it is interesting to find significant biomarkers between two groups while controlling error rate such as false discovery rate (FDR). Over the last few decades, a lot of methods that control local false discovery rate have been developed, ranging from one-dimensional to k-dimensional FDRdoi:10.3390/metabo11010053 pmid:33466792 fatcat:rpbv3mol3vh3xkapccua2a22ei