getFitsDropout: Get drop-out model fits

In LineagePulse: Differential expression analysis and model fitting for single-cell RNA-seq data

Description

Return drop-out model fits per gene and cell as matrix for chosen models.

Usage

getFitsDropout(lsMuModel, lsDropModel, vecGeneIDs = NULL)

Arguments

lsMuModel	(list) Object containing description of gene-wise mean parameter models.
lsDropModel	(list) Object containing description of cell-wise drop-out parameter models.
vecGeneIDs	(vector of strings) [Default NULL] Gene IDs for which posteriors of drop-out are to be computed.

Value

(numeric matrix genes x cells) Drop-out rate fits.

Author(s)

David Sebastian Fischer

Examples

lsSimulatedData <- simulateContinuousDataSet(
    scaNCells = 20,
    scaNConst = 2,
    scaNLin = 2,
    scaNImp = 2,
    scaMumax = 100,
    scaSDMuAmplitude = 3,
    vecNormConstExternal=NULL,
    vecDispExternal=rep(20, 6),
    vecGeneWiseDropoutRates = rep(0.1, 6))
objLP <- runLineagePulse(
    counts = lsSimulatedData$counts,
    dfAnnotation = lsSimulatedData$annot,
    strMuModel = "impulse")
# Get drop-out rate fits on alternative model:
# Use H1 model fits.
vecDropoutFits <- getFitsDropout(
     lsMuModel = lsMuModelH1(objLP),
     lsDropModel = lsDropModel(objLP),
     vecGeneIDs = rownames(lsSimulatedData$counts)[1])

LineagePulse documentation built on Nov. 8, 2020, 7:01 p.m.