# Reference

## All functions
`Bulk_Read_Counts` | Parekh et al. 2016: Gene Expression Matrices
`CELseq2_Gene_Read_Counts` `CELseq2_Gene_UMI_Counts` `DropSeq_Gene_Read_Counts` `DropSeq_Gene_UMI_Counts` `MARSseq_Gene_Read_Counts` `MARSseq_Gene_UMI_Counts` `SCRBseq_Gene_Read_Counts` `SCRBseq_Gene_UMI_Counts` `SmartSeq_Gene_Read_Counts` `SmartSeq2_Gene_Read_Counts` | Ziegenhain et al. 2017: Gene Expression Matrices
`GeneLengths_hg19` | Parekh et al. 2016: Gene Lengths
`GeneLengths_mm10` | Ziegenhain et al. 2017: Gene Lengths
`Setup()` | Setup options for RNA-seq count simulations
`CELseq2_SpikeIns_Read_Counts` `CELseq2_SpikeIns_UMI_Counts` `DropSeq_SpikeIns_Read_Counts` `DropSeq_SpikeIns_UMI_Counts` `MARSseq_SpikeIns_Read_Counts` `MARSseq_SpikeIns_UMI_Counts` `SCRBseq_SpikeIns_Read_Counts` `SCRBseq_SpikeIns_UMI_Counts` `SmartSeq_SpikeIns_Read_Counts` `SmartSeq2_SpikeIns_Read_Counts` | Ziegenhain et al. 2017: Spike-Ins Expression
`CELseq2_SpikeInfo` `MARSseq_SpikeInfo` `SCRBseq_SpikeInfo` `SmartSeq_SpikeInfo` `SmartSeq2_SpikeInfo` | Ziegenhain et al. 2017: Spike-Ins Information
`estimateParam()` | Estimate simulation parameters
`estimateSpike()` | Estimate simulation parameters for spike-ins
`evaluateDE()` | Compute the confusion matrix-related quantities from simulation results
`evaluateDist()` | Model Diagnostics for RNAseq Data
`evaluateROC()` | Receiver operator characteristics of simulation results
`evaluateSim()` | Compute the performance related metrics from simulation results.
`plotEvalDE()` | Visualize power assessment
`plotEvalDist()` | Visualize distribution assessment
`plotEvalROC()` | Visualize error rate curves and associated summary statistics
`plotEvalSim()` | Visualize power assessment
`plotParam()` | Visualize distributional characteristics of RNA-seq experiment
`plotSpike()` | Visualize distributional characteristics of spike-ins
`plotTime()` | Visualize computational time
`printEvalDE()` | Summary table of power assessment
`simulateDE()` | Simulate Differential Expression Pipeline