Benchmark of false discovery control on Rosette simulation. Variants are ranked by hypothesis testing (adjusted p-values or lfsr ). The false discovery rate at each rank is computed as the proportion of neutral variants assuming all the variants till the rank cutoff are called significant. R is the number of replicates and T is the number of selection rounds. MET data is used for negative selection and OCT1 data for positive selection. Ideally, the line would be flat at 0 until the rank where all variants with true effects are discovered. (DiMSum can only process two time points and thus is disadvantaged in experiments with more than two time points, or one selection round)
