biosign-class {biosigner} | R Documentation

## Class "biosign"

### Description

The biosigner object class

### Slots

`methodVc`

  character vector: selected classifier(s) ('plsda', 'randomforest', or 'svm')

`accuracyMN`

  numeric matrix: balanced accuracies for the full models, and the models restricted to the 'S' and 'AS' signatures

`tierMC`

  character matrix: contains the tier ('S', 'A', 'B', 'C', 'D', or 'E') of each feature for each classifier

`yFc`

  factor with two levels: response factor

`modelLs`

  list: selected classifier(s) trained on the subset restricted to the 'S' features

`signatureLs`

  list: 'S' signatures for each classifier

`xSubMN`

  matrix: dataset restricted to the 'S' tier

`AS`

  list: 'AS' signatures and corresponding trained classifiers, in addition to the dataset restricted to tiers 'S' and 'A' ('xMN') and the labels ('yFc')

`eset`

  ExpressionSet: when 'biosign' has been applied to an ExpressionSet, the instance with additional columns in fData containing the selected features is stored here

### Objects from the Class

Objects can be created by calls of the form `new("biosign", ...)` or by calling the `biosign` function

### Author(s)

Philippe Rinaudo and Etienne Thevenot (CEA)

### See Also

`biosign`

### Examples

    ## loading the diaplasma dataset

    data(diaplasma)
    attach(diaplasma)

    ## restricting to a smaller dataset for this example

    featureSelVl <- variableMetadata[, "mzmed"] >= 490 & variableMetadata[, "mzmed"] < 500
    dataMatrix <- dataMatrix[, featureSelVl]
    variableMetadata <- variableMetadata[featureSelVl, ]

    ## signature selection for all 3 classifiers
    ## a bootI = 5 number of bootstraps is used for this example
    ## we recommend to keep the default bootI = 50 value for your analyzes

    set.seed(123)
    diaSign <- biosign(dataMatrix, sampleMetadata[, "type"], bootI = 5)

    detach(diaplasma)

[Package biosigner version 1.16.0 Index]