Description Objects Slots Methods Author(s) References See Also Examples

S4 class for storing the result of an association test for a single genomic region

Objects of this class are created by calling `assocTest`

for a single genomic region.

The following slots are defined for `AssocTestResult`

objects:

`type`

:type of null model on which the association test was based

`samples`

:character vector with sample names (if available, otherwise empty)

`kernel`

:kernel that was used for the association test

`dim`

:dimensions of genotype matrix that was tested

`weights`

:weight vector that was used; empty if no weighting was performed

`width`

:tolerance radius parameter that was used for position-dependent kernels

`method`

:method(s) used to compute p-values; a single character string if no resampling was done, otherwise a list with two components specifying the p-value computation method for the test's p-value and the resampled p-values separately.

`correction`

:a logical vector indicating whether the small sample correction was carried out (first component

`exact`

is`TRUE`

) and/or higher moment correction was carried out (second component`resampling`

is`TRUE`

).`Q`

:test statistic

`p.value`

:the test's p-value

`Q.resampling`

:test statistics for sampled null model residuals

`p.value.resampling`

:p-values for sampled null model residuals

`p.value.resampled`

:estimated p-value computed as the relative frequency of p-values of sampled residuals that are at least as significant as the test's p-value

`call`

:the matched call with which the object was created

- show
`signature(object="AssocTestResult")`

: displays the test statistic and the p-value along with the type of the null model, the number of samples, the number of SNVs, and the kernel that was used to carry out the test.

Ulrich Bodenhofer [email protected]

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

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ```
## load genome description
data(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 entire genotype matrix
res <- assocTest(Z, nm.lin)
show(res)
## perform association test for subset of genotype matrix
res <- assocTest(Z[, 50:100], nm.lin)
show(res)
``` |

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