varianceOnto: The variance of the gaussian learning noise at individual...

In fspetale/fgga: Hierarchical ensemble method based on factor graph

The variance of the gaussian learning noise at individual Ontology-terms

Description

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

Usage

varianceOnto(tableOntoTerms, dxCharacterized, kFold, graphOnto, rootNode,
            kernelSVM = "radial")

Arguments

tableOntoTerms	A binary matrix with ‘n’ protein coding genes (rows) by ‘m’ cross-Ontology 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.
graphOnto	A graphNEL graph with ‘m’ cross-Ontology 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 \eta_i can be estimated using a validation dataset of positively annotated samples.

Value

A vector named with the variance of each cross-Ontology node.

Author(s)

Flavio E. Spetale <[e-mail]>

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 <- varianceOnto(tableOntoTerms = myTableGO,
                            dxCharacterized = CfData[["dxCf"]],
                            kFold = 2, graphOnto = mygraphGO,
                            rootNode = rootGO, kernelSVM = "radial")

fspetale/fgga documentation built on Jan. 29, 2024, 6:53 p.m.