DESeq-methods: Extension for the DESeq package

In easyRNASeq: Count summarization and normalization for RNA-Seq data

Description

• multivariateConditions is simply an accessor for the multivariateConditions slot of a CountDataSet object

• plotDispLSD is a function similar to plotDispEsts that adds a density estimate as a colored heatmap from grey (few) to yellow (many).

• plotDispersionEstimates offers the functionality to plot the dispersion estimate as described in the DESeq vignette.

Usage

multivariateConditions(obj)
plotDispLSD(obj, name = NULL, ymin,
linecol = "#00000080", xlab = "mean of normalized counts",
ylab = "dispersion", log = "xy", cex = 0.45, ...)
plotDispersionEstimates(obj,cond,log,...)

Arguments

obj	An object of class CountDataSet.
cex	The standard plot.default parameter.
cond	A character string describing the first condition.
linecol	Defines the line color.
log	A character string passed onto plot.default.
name	Argument passed to the DESeq fitInfo function.
xlab	The standard plot.default parameter.
ylab	The standard plot.default parameter.
ymin	A numeric value defining the lower limit for the y axis.
...	Additional plotting parameters.

Value

• multivariateConditions returns a boolean describing whether the data to analyze is multivariate or not

• plotDispLSD and plotDispersionEstimates returns nothing

Author(s)

Nicolas Delhomme, Bastian Schiffthaler

See Also

CountDataSet plotDispEsts

Examples

	## Not run: 
	# these are helper function for the DESeq package
	# refer to its vignette first
	cds <- newCountDataSet(countData,conditions)
	cds <- estimateSizeFactors(cds)
	cds <- estimateDispersions(cds)
	mVar <- multivariateConditions(cds)
	plotDispersionEstimates(cds,conditions[1])
	
## End(Not run)

easyRNASeq documentation built on April 30, 2020, 2 a.m.