varianceGO {fgga} | R Documentation

## The variance of the gaussian learning noise at individual GO-terms

### Description

varianceGO estimates the variance of gaussian distributions modeling the additive learning noise that corrupts ideal GO-term predictions.

### Usage

    varianceGO(tableGOs, dxCharacterized, kFold, graphGO, rootNode,
                kernelSVM = "radial")

### Arguments

`tableGOs` | A binary matrix with ‘n’ protein coding genes (rows) by ‘m’ GO node labels (columns).
`dxCharacterized` | A data frame with ‘n’ protein coding genes (rows) by ‘f’ features (columns).
`kFold` | An integer for the number of folds.
`graphGO` | A graphNEL graph with ‘m’ GO node labels.
`rootNode` | A character indicating the root of the graph.
`kernelSVM` | The kernel used to calculate the variance (default: radial).

### Details

Under the assumption of symmetrical (Gaussian) conditional probability distributions for observable variable node predictions y_i over a hidden variable node annotations x_i, variances η_i can be estimated using a validation dataset of positively annotated samples.

### Value

A vector named with the variance of each GO node.

### Author(s)

Flavio E. Spetale and Javier Murillo <spetale@cifasis-conicet.gov.ar>

### References

Spetale FE, Tapia E, Krsticevic F, Roda F, Bulacio P (2016). A Factor Graph Approach to Automated GO Annotation. PLOS ONE 11(1): e0146986

### Examples

    data(CfData)

    mygraphGO <- as(CfData[["graphCfGO"]], "graphNEL")

    rootGO <- leaves(mygraphGO, "in")

    mygraphGO <- subGraph(c("GO:0140110", "GO:0098772", "GO:0003674"), mygraphGO)

    myTableGO <- CfData[["tableCfGO"]][
                        CfData[["indexGO"]]$indexTrain,
                        c("GO:0140110", "GO:0098772", "GO:0003674")]

    varianceGOs <- varianceGO(tableGOs = myTableGO,
                                dxCharacterized = CfData[["dxCf"]],
                                kFold = 2, graphGO = mygraphGO,
                                rootNode = rootGO, kernelSVM = "radial")

[Package fgga version 1.2.0 Index]