sort-methods {podkat} | R Documentation

## Sort Association Test Results

### Description

Rearrange association test results according to sort criterion

### Usage

    ## S4 method for signature 'AssocTestResultRanges'
    sort(x, decreasing=FALSE,
         sortBy=c("p.value", "p.value.adj", "p.value.resampled",
                  "p.value.resampled.adj", "genome"))

### Arguments

`x` | object of class `AssocTestResultRanges`
`decreasing` | logical indicating if sorting should be done in decreasing order
`sortBy` | sort criterion (see details below)

### Details

The function `sort` takes an `AssocTestResultRanges` object `x` and returns a new object of the same class, but with the regions rearranged according to the sort criterion `sortBy`. As an example, if `sortBy` is “p.value” regions are sorted according to raw p-values in ascending order, analogously for the choices “p.value.adj”, “p.value.resampled”, and “p.value.resampled.adj”. If `sortBy` is “genome”, the regions are arranged along the genome in the same way as a `GRanges` object would be sorted. If `decreasing` is `TRUE`, the order is reversed.

### Value

an `AssocTestResultRanges` object;

### Author(s)

Ulrich Bodenhofer bodenhofer@bioinf.jku.at

### References

http://www.bioinf.jku.at/software/podkat

### See Also

`AssocTestResultRanges`

### Examples

    ## load genome description
    data(hgA)

    ## partition genome into overlapping windows
    windows <- partitionRegions(hgA)

    ## load genotype data from VCF file
    vcfFile <- system.file("examples/example1.vcf.gz", package="podkat")
    Z <- readGenotypeMatrix(vcfFile)

    ## read phenotype data from CSV file (continuous trait + covariates)
    phenoFile <- system.file("examples/example1lin.csv", package="podkat")
    pheno <-read.table(phenoFile, header=TRUE, sep=",")

    ## train null model with all covariates in data frame 'pheno'
    nm.lin <- nullModel(y ~ ., pheno)

    ## perform association test for multiple regions
    res <- assocTest(Z, nm.lin, windows)

    ## perform multiple testing correction
    res.adj <- p.adjust(res)

    ## show sorted results (default: by raw p-value)
    as(sort(res), "GRanges")
    print(sort(res), sortBy="none")

    ## show results sorted by adjusted p-value
    as(sort(res.adj, sortBy="p.value.adj"), "GRanges")
    print(sort(res.adj, sortBy="p.value.adj"), sortBy="none")

[Package podkat version 1.12.0 Index]