| estimatelog2FoldChanges {DEXSeq} | R Documentation |
This function calculates the fold changes (on log2 scale) between the different conditions. It calculates them from the coefficients of a GLM that fits the read counts to a variable of the experimental design specified by the user (see below, parameter "fitExpToVar").
estimatelog2FoldChanges(ecs, fitExpToVar="condition",
denominator="", getOnlyEffects=FALSE, averageOutExpression=TRUE,
nCores=1, quiet=FALSE, file="")
ecs |
An ExonCountSet object. |
fitExpToVar |
A variable contained in |
denominator |
A value of the sample annotation (e.g. condition) to use as a denominator in the log2 fold change. As a default, the function will take the annotation of the first sample |
getOnlyEffects |
If TRUE, the raw effects are added as columns to the feature data and any operation (log2) is performed with them. |
averageOutExpression |
The default, TRUE, gives back splicing effects. If FALSE, the gene expression effects won't be substracted. |
nCores |
Number of CPU cores to be used to estimate the dispersions.
The |
quiet |
If TRUE, no progress report is shown. In case the session is not an interactive and progress report is wanted, add a file name below. |
file |
A file name to write the progress reports. If file="", output will be written to the standard output connection. |
## Not run:
data("pasillaExons", package="pasilla")
pasillaExons <- estimateSizeFactors( pasillaExons )
pasillaExons <- estimateDispersions( pasillaExons )
pasillaExons <- fitDispersionFunction( pasillaExons )
pasillaExons <- estimatelog2FoldChanges( pasillaExons )
## End(Not run)