GEVASummary-class: GEVA Summary-Variation Table
In sbcblab/geva: Gene Expression Variation Analysis (GEVA)

The GEVASummary class represents the calculation results for summary and variation from a GEVAInput.

This class inherits from SVTable.

A GEVASummary object

sv: numeric matrix composed by two columns: S (summary) and V (variation)
(Inherited from SVTable)
inputdata: GEVAInput-class with the data input
sv.method: Names of the statistical methods used to summarize data
info: list with additional information

(See also the inherited methods from SVTable)

Conversion and coercion

as.expression(x, ginput, ...): Gets the expression that reproduces this GEVASummary object, including function parameters used by geva.summary. The ginput argument is optional but can be specified to replace the internal GEVAInput
as.matrix(x, ...): Equivalent to sv(x)

Grouping

groupsets(object) <- value: Converts this instance to GEVAGroupedSummary and sets the list of GEVAGroupSet objects. Can be used with $<name> to specify the object name in the list. If value is a GEVAGroupSet, inserts the element and sets the name based on the value call
groupsets(object): Gets the list of GEVAGroupSet objects attached to this instance. Only applicable for GEVAGroupedSummary objects

Plotting

plot(x, y, ...): Draws a SV-plot. The horizontal axis is for summary (S) and the vertical axis is for variation (V)

Properties

analysis.params(gobject): Returns a list of analysis parameters passed to geva.summarize to obtain this object
get.summary.method(x): Gets a character for the summarization method name
get.variation.method(x): Gets a character for the variation calculation method name

Sub-slot accessors

factors(object) <- value: Sets the value to the factor slot in the internal GEVAInput
factors(object): Gets the factor defined in the factors slot in the internal GEVAInput
featureTable(object): Gets the data.frame from the ftable slot in the internal GEVAInput
infolist(object, field = NULL, ...): Gets the list from the info slot.
If recursive is TRUE, appends the contents from the info slot in the internal GEVAInput
inputvalues(object): Gets the matrix from the values slot in the internal GEVAInput
inputweights(object, normalized): Gets the matrix from the weights slot in the internal GEVAInput