A <code><links4class>GRanges</links4class></code> object defining a
  minimalistic artificial human chromosome with 200,000 bp length

datasets

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.

Ulrich Bodenhofer

podkat

Position-Dependent Kernel Association Test

hgA function

Real human genome-based examples would require the supply
  of massive data and would require lengthy computation
  times. Therefore, the examples supplied with this package are based on
  a small single-chromosome artificial genome. The
  <code><links4class>GRanges</links4class></code> object <code>hgA</code> provides a description
  of this artificial genome that can be used for further processing,
  e.g. by the <code><a href="/link/partitionRegions?package=podkat&version=1.4.2" rd-options="" data-mini-rdoc="podkat::partitionRegions">partitionRegions</a></code> function.

format

A <code><linkS4class>GRanges</linkS4class></code> object defining a
  minimalistic artificial human chromosome with 200,000 bp length

hgA: Artificial Human Chromosome for Testing Purposes

Description

Usage

Arguments

format

References

See Also

Examples