computeModelFits: Return a gene x sample and gene x time point (for each...

In YosefLab/ImpulseDE2: Differential expression analysis of longitudinal count data sets

Return a gene x sample and gene x time point (for each condition) matrix with model fits.

Description

Return a gene x sample and gene x time point (for each condition) matrix with model fits.

Usage

computeModelFits(objectImpulseDE2)

Arguments

objectImpulseDE2

(instance of class ImpulseDE2Object) ImpulseDE2 output object to create heatmap from.

Value

• sample (data.frame) Data frame with model fit by gene and sample.

• case (data.frame) Data frame with model fit by gene and time point in case condition

• control (data.frame) Data frame with model fit by gene and time point in control condition

Author(s)

David Sebastian Fischer

See Also

Called seperately by user.

Examples

lsSimulatedData <- simulateDataSetImpulseDE2(
vecTimePointsA   = rep(seq(1,8),3),
vecTimePointsB   = NULL,
vecBatchesA      = do.call(c, lapply(c("A", "B", "C"), function(x) rep(x, 8))),
vecBatchesB      = NULL,
scaNConst        = 0,
scaNImp          = 50,
scaNLin          = 0,
scaNSig          = 50,
scaMuBatchEffect = 1, 
scaSDBatchEffect = 1)
objectImpulseDE2 <- runImpulseDE2(
matCountData    = lsSimulatedData$matObservedCounts, 
dfAnnotation    = lsSimulatedData$dfAnnotation,
boolCaseCtrl    = FALSE,
vecConfounders  = c("Batch"),
boolIdentifyTransients = TRUE,
scaNProc        = 1 )
modelFits <- computeModelFits(objectImpulseDE2=objectImpulseDE2)
head(modelFits$case)

YosefLab/ImpulseDE2 documentation built on Sept. 17, 2022, 2:45 a.m.