This package provides an association test that is capable of dealing with very rare and even private variants. This is accomplished by a kernel-based approach that takes the positions of the variants into account. The test can be used for pre-processed matrix data, but also directly for variant data stored in VCF files. Association testing can be performed whole-genome, whole-exome, or restricted to pre-defined regions of interest. The test is complemented by tools for analyzing and visualizing the results.
|Date of publication||None|
|Maintainer||Ulrich Bodenhofer <email@example.com>|
|License||GPL (>= 2)|
assocTest-methods: Perform Association Test
AssocTestResult-class: Class 'AssocTestResult'
AssocTestResultRanges-class: Class 'AssocTestResultRanges'
computeKernel: Compute Kernel Matrix
filterResult-methods: Filter Association Test Results According to p-Values or...
GenotypeMatrix-class: Class 'GenotypeMatrix'
genotypeMatrix-methods: Constructors for Creating 'GenotypeMatrix' Objects
hgA: Artificial Human Chromosome for Testing Purposes
NullModel-class: Class 'NullModel'
nullModel-methods: Create Null Model for Association Test
p.adjust-methods: Adjust p-Value for Multiple Tests
partitionRegions-methods: Partition Genomic Regions
plot-methods: Plotting functions
podkat-package: PODKAT Package
print-methods: Print Association Test Results
qqplot-methods: Quantile-Quantile Plots
readGenotypeMatrix-methods: Read from VCF File
readRegionsFromBedFile: Read Genomic Regions from BED File
readSampleNamesFromVcfHeader: Read Sample Names from VCF File Header
readVariantInfo-methods: Read information about variants from VCF file
sort-methods: Sort Association Test Results
split-methods: Split 'GRanges' Object
unmasked-datasets: Unmasked Regions of Human Genomes
unmaskedRegions: Extract Unmasked Regions from 'MaskedBSgenome' Object
VariantInfo-class: Class 'VariantInfo'
weightFuncs: Weighting Functions
weights-methods: Extract Contribution Weights of Variants