## S3 method for class 'AssocTestResult':
weights(object, Z, model)
## S3 method for class 'AssocTestResultRanges':
weights(object, Z, model, limit=20, sex=NULL)AssocTestResult AssocTestResultRanges GenotypeMatrix TabixFile, or a
character string with the file name of a VCF fileNullModel Inf or non-numeric value like NA or NULL
to disable limitation. Do this with caution, in particular, when
reading from a VCF file, as reading of excessively large regions
from VCF files may take very long or even kill the R session because
of excessive memory comsumption!NULL, all samples are treated the same
without any modifications; if sex is a factor with levels
F (female) and M (male) that is as long as
the number of samples in model, this argument is
interpreted as the sex of the samples. In this case, the genotypes
corresponding to male samples are
doubled before further processing. This is designed for mixed-sex
analyses of the X chromosome outside of the pseudoautosomal
regions.GRanges GRangesList weights
method allows for finding out the individual contributions each of the
variants made to the test statistic. This computation is only possible
for kernels computeKernel). If called for an object, a Z, and a model, weights returns a
variantInfo(Z) along with two numerical metadata columns named
If weights is called for an
object,
a second argument Z that is an object of class
TabixFile, or a character string with the
name of a VCF file, and a model, the contribution weights described above
are computed for each region in object. In this case, the
method returns a object has regions, where each list component is
a
It is essential for weights to work correctly that
object is actually the result of an association test between
Z and model. If called for objects that actually do not
belong to each other, the results are void. The method is implemented
such that all possible checks are made that possibly detect
inconsistencies between the input objects. However, the final
responsibility is left to user to make sure that all data are
consistent. Special caution is necessary if weights is run
for an AssocTestResultRanges object that has
been obtained by merging multiple c method. The c method performs several checks
to ensure consistency of association test parameters among the merged
results, but the sex parameter is an exception: if it appears
to be inconsistent among the results to merge, it is omitted from the
merged object (see also
The weights method needs to re-evaluate some computations of
the association test. In case it is called for Z being a
TabixFile object or file name of a VCF file,
weights even needs to re-read the genotype data from the file.
Therefore, the method has a safety limit not to process too many
regions (see limit argument described above).
assocTest, AssocTestResult,
AssocTestResultRanges, nullModel,
NullModel computeKernel,
GenotypeMatrix p.adjust,
filterResult## 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'
model <- nullModel(y ~ ., pheno)
## perform association test
res <- assocTest(Z, model, windows)
## perform multiple testing correction and filter for
## significant regions
res <- filterResult(p.adjust(res), filterBy="p.value.adj")
## compute contributions
contrib <- weights(res, Z, model)
contrib
## extract most indicative variants
filterResult(contrib)
## plot contributions
plot(contrib[[1]], "weight.raw")
plot(contrib[[1]], "weight.contribution", type="b", alongGenome=TRUE)