p.adjust.SFL {mvGST} | R Documentation

## Short Focus Level adjustment

### Description

Takes a named numeric vector of raw p-values as input and returns the Short Focus Level adjusted p-values, where the adjustment is based on controlling the FWER at a specified level within the structure of the GO graph.

### Usage

    p.adjust.SFL(rawp, ontology=c("BP","CC","MF"),
        focus='rn', ancestors, offspring, trace=FALSE,
        recycle=TRUE, sig.level=0.05)

### Arguments

`rawp` | named numeric vector of p-values where the names correspond to the GO ID for which the provided p-values correspond to the given GO Term. These must be 'two-sided' p-values, i.e., from a two-sided test.
`ontology` | The ontology of interest. Must be one of 'BP', 'CC', or 'MF'. All names of rawp must be from the same ontology. Defaults to 'BP'.
`focus` | the focus level of interest. Default is set at the root node, the logical place to start if there is no better place to start.
`ancestors` | named lists corresponding to the ancestor and offspring structure of all named GO IDs in rawp. These are optional, and simply result in faster computation of the adjusted p-values if they are already available from the R session when p.adjust.SFL is called.
`offspring` | named lists corresponding to the ancestor and offspring structure of all named GO IDs in rawp. These are optional, and simply result in faster computation of the adjusted p-values if they are already available from the R session when p.adjust.SFL is called.
`trace` | logical denoting whether or not progress about the algorithm is output to the user. Defaults to FALSE.
`recycle` | logical determining whether or not to recycle any threshold corresponding to a rejected leaf node back into the GO graph. Defaults to TRUE, as it can result in greater power for the Short Focus Level method at a slight increase to the computational burden.
`sig.level` | numeric value at which to control the family-wise error rate within the structure of the GO graph.

### Details

To access the tutorial document for this package, type in R: `vignette("mvGST")`

### Value

returns the adjusted p-values with naming and ordering identical to the original "rawp" values.

### Author(s)

John R. Stevens and Garrett Saunders

### References

Saunders G., Stevens J.R., and Isom S.C. "A shortcut for multiple testing on the directed acyclic graph of Gene Ontology." BMC Bioinformatics 2014 (under review).

Saunders, G., 2014. "Family-wise error rate control in QTL mapping and gene ontology graphs with remarks on family selection." PhD thesis, Utah State University, Department of Mathematics and Statistics. http://digitalcommons.usu.edu/etd/2164/

### Examples

    # Get GO terms of interest
    library(GOstats); library(annotate)
    GO.vec <- c("GO:0001775","GO:0007275")
    g <- GOGraph(GO.vec, GOBPPARENTS)
    g <- removeNode("all",g)
    GOids <- names(nodes(g))

    # Get p-values for all GO terms of interest
    # (here, simulated for demonstration)
    # Make sure names are GO term IDs
    set.seed(1)
    rawp <- rbeta(length(GOids), .2, 1)
    names(rawp) <- GOids

    # P-value adjustment using Short Focus Level
    padj <- p.adjust.SFL(rawp, ontology='BP')
    head(padj)
    # These are in the same order as rawp, with
    # names corresponding to GO terms.
    # Calling GO terms significant when padj is
    # less than alpha controls the FWER at alpha,
    # within the context of the GO graph.

    # See package vignette for larger examples with discussion:
    #    vignette("mvGST")

[Package mvGST version 1.12.2 Index]