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Hum Hered. 2007;64(1):45-51. Epub 2007 Apr 27.

An R package for analysis of whole-genome association studies.

Author information

1
Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK. david.clayton@cimr.cam.ac.uk

Abstract

OBJECTIVE:

To provide data classes and methods to facilitate the analysis of whole genome association studies in the R language for statistical computing.

METHODS:

We have implemented data classes in which each genotype call is stored as a single byte. At this density, data for single chromosomes derived from large studies and new high-throughput gene chip platforms can be handled in memory. We use the object-oriented programming model introduced with version 4 of the S-plus package, usually termed 'S4 methods'.

RESULTS:

At the current state of development the package only supports population-based studies, although we would hope to provide support for family-based studies soon. Both quantitative and qualitative phenotypes may be analysed. Flexible association testing functions are provided which can carry out single SNP tests which control for potential confounding by quantitative and qualitative covariates. Tests involving several SNPs taken together as 'tags' are also supported. Efficient calculation of pair-wise linkage disequilibrium measures is implemented and data input functions include a function which can download data directly from the international HapMap project website.

PMID:
17483596
DOI:
10.1159/000101422
[Indexed for MEDLINE]

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