| analyze_dataset | analyze_dataset: Basically performs preprocessing and then returns analyzed RNASeq dataset (diff. expression) , i.e. the DESeq2 result whose p-values and baseMean statistics can then be used with IHW |
| bh | bh: Wrapper for Benjamini Hochberg |
| bonf | bonf: Wrapper for Bonferroni |
| clfdr | clfdr: Cai's local fdr based method |
| continuous_wrap | Benchmarking wrapper: Given a multiple testing method, convert it so that it takes a simulation object (see simulation function) and a nominal level alpha as inputs |
| ddhf | ddhf: Greedy independent filtering |
| du_ttest_sim | t-test simulation: Simulate rowwise t-tests |
| du_ttest_sim_fun | t-test simulation: Simulate rowwise t-tests |
| gbh | gbh: Grouped Benjamini Hochberg |
| ihw_5fold | IHW wrappers |
| ihw_5fold_reg | IHW wrappers |
| ihw_bonf_5fold_reg | IHW wrappers |
| ihw_ecdf_5fold | IHW wrappers |
| ihw_naive | IHW wrappers |
| ihw_storey_5fold | IHW wrappers |
| lsl_gbh | gbh: Grouped Benjamini Hochberg |
| lsl_pi0_est | LSL (Least-Slope) pi0 estimator |
| null_sim | Null simulation: Generate uniformly distributed p-values and covariates |
| null_sim_fun | Null simulation: Generate uniformly distributed p-values and covariates |
| pretty_legend | helper function to create nice legends |
| run_evals | run_evals: Main function to benchmark FDR methods on given simulations. |
| scott_fdrreg | scott_fdrreg: Wrapper for FDR regression (https://github.com/jgscott/FDRreg) |
| storey_qvalue | storey_qvalue: Wrapper for Storey's qvalue package |
| stratified_bh | stratified_bh: Stratified Benjamini Hochberg |
| tst_gbh | gbh: Grouped Benjamini Hochberg |
| tst_pi0_est | TST (Two-Step) pi0 estimator |
| wasserman_normal_prds_sim | Normal PRDS simulation: Covariate is effect size under alternative, there are latent factors driving PRDS correlations among hypotheses |
| wasserman_normal_prds_sim_fun | Normal PRDS simulation: Covariate is effect size under alternative, there are latent factors driving PRDS correlations among hypotheses |
| wasserman_normal_sim | Normal simulation: Covariate is effect size under alternative |
| wasserman_normal_sim_fun | Normal simulation: Covariate is effect size under alternative |