frma (version 1.24.0)

frmaExpressionSet-class: Class to Contain and Describe High-Throughput Expression Level Assays preprocessed with fRMA

Description

This is a class representation for fRMA-preprocessed expression data. frmaExpressionSet class is derived from ExpressionSet, and requires a matrix named exprs and optionally matrices named se.exprs, weights, and residuals.

Extends

Extends class ExpressionSet.

Creating Objects

new("frmaExpressionSet", exprs = new("matrix"), se.exprs = new("matrix"), weights=new("matrix"), residuals=new("matrix"), randomeffects=new("matrix"), phenoData = new("AnnotatedDataFrame"), featureData = new("AnnotatedDataFrame"), experimentData = new("MIAME"), annotation = new("character"), ...) This creates a frmaExpressionSet with assayData implicitly created to contain exprs and se.exprs. The only required named arguments is exprs. Three optional named matrices, weights, residuals, and randomeffects can be added to the object. new("frmaExpressionSet", assayData = assayDataNew(exprs=new("matrix"),se.exprs=new("matrix")), weights=new("matrix"), residuals=new("matrix"), randomeffects=new("matrix"), phenoData = new("AnnotatedDataFrame"), featureData = new("AnnotatedDataFrame"), experimentData = new("MIAME"), annotation = new("character"), ...) This creates a frmaExpressionSet with assayData provided explicitly. In this form, the only required named argument is assayData. Three optional named matrices, weights, residuals, and randomeffects can be added to the object.

Slots

se.exprs:

standard errors for the expression estimates

weights:

weights used in the summarization step

residuals:

residuals from fitting the probe-level model

randomeffects:

random effect estimates from fitting the probe-level model using random effect summarization

Inherited from ExpressionSet:

assayData:

Contains matrices with equal dimensions, and with column number equal to nrow(phenoData). assayData must contain a matrix exprs with rows representing features and columns representing samples. It may also contain a matrix se.exprs containing standard errors.

phenoData:

See eSet

annotation:

See eSet

featureData:

See eSet

experimentData:

See eSet

Methods

Class-specific methods:

se.exprs(frmaExpressionSet)

Access elements named se.exprs in the AssayData-class slot.

weights(frmaExpressionSet)

Access elements named weights

residuals(frmaExpressionSet)

Access elements named residuals

randomeffects(frmaExpressionSet)

Access elements named randomeffects

For derived methods (see ExpressionSet).

See Also

eSet-class, ExpressionSet-class, frma.

Examples

# create an instance of frmaExpressionSet
new("frmaExpressionSet")