Power_Cont: Run DE analysis by using MAST. Here we output two result...

In suke18/POWSC: Simulation, power evaluation, and sample size recommendation for single cell RNA-seq

Description

Run DE analysis by using MAST. Here we output two result tables corresponding to two forms of DE genes. These parameters include four gene-wise parameters and two cell-wise parameters.

Usage

Power_Cont(
  DErslt,
  simData,
  alpha = 0.1,
  delta = 0.5,
  strata = c(0, 10, 2^(seq_len(4)) * 10, Inf)
)

Arguments

DErslt	is from the DE analysis by MAST
simData	is the corresponding simulated scRNA-seq dataset (SingCellExperiment)
alpha	is the cutoff for the fdr which can be modified
delta	or the lfc is the cutoff (=0.5) used to determined the high DE genes for Form II
strata	can be modified by the user. By default, it is (0, 10], (10, 20], (20, 40], (40, 80], (80, Inf]

Value

a list of metrics for power analysis such as: stratified targeted power and marginal power.

Examples

data("es_mef_sce")
sce = es_mef_sce[, colData(es_mef_sce)$cellTypes == "fibro"]
set.seed(123)
rix = sample(1:nrow(sce), 500)
sce = sce[rix, ]
estParas = Est2Phase(sce)
simData = Simulate2SCE(n=500, estParas1 = estParas, estParas2 = estParas)
DErslt = runDE(simData$sce)
Cont_pow = Power_Cont(DErslt, simData)

suke18/POWSC documentation built on April 2, 2021, 4:34 a.m.