Version 1.2.3 (2020-6-30)

Adapt methods of moments estimation of mean, dispersion and dropout during simulation.

Version 1.2.2 (2020-6-18)

Ensuring compability with R version 4.0 (e.g. deprecated DEDS Bioconductor package)
Adapt log fold change model matrix addition
Adding log fold changes to fraction of replicates per group (option p.G in Setup())

Downsampling of count matrices using binomial thinning implemented in estimateParam() (UMI-read ratio estimation) and simulateDE().
Setup of DE simulations now in one function (Setup()) instead of two.
estimateParam() with additional filtering options based on quality control checkup of scater package.
implement sctransform as a single cell normalisation method.

simulateDE() using SCnorm scaling factors as weights in limma-trend, limma-voom.

simulateDE() now with the option to perform DE testing on filtered/imputed counts (option DEFilter)

simulation of batch effects (see options p.B, bLFC and bPattern in DESetup() and simulateCounts())
simulation of spike-in expression (see estimateSpike , plotSpike and option spikeIns in simulateDE and simulateCounts())
simulation of multiple sample groups (e.g. single cell populations) with simulateCounts()
imputation and prefiltering options prior to normalisation in DE power simulations added (scImpute, scone, Seurat, DrImpute, SAVER)
additional normalisation options and DE tools (esp. for single cells) included in simulateDE()
evaluation of simulation setup using estimated versus true value comparisons of library size factors and log2 fold changes in evaluateSim() and plotEvalSim()
increased flexibility in preprocessing for distribution evaluation in evaluateDist()