Biostatistics Advance Access originally published online on December 22, 2006
Biostatistics 2007 8(2):485-499; doi:10.1093/biostatistics/kxl042
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Exploration, normalization, and genotype calls of high-density oligonucleotide SNP array data
Department of Biostatistics, Johns Hopkins University, Baltimore, MD 21205, USA
Department of Statistics, University of California, Berkeley, CA, USA
Division of Genetics and Bioinformatics, Walter and Eliza Hall Institute, Melbourne, Australia and Department of Statistics, University of California, Berkeley, CA, USA
Department of Biostatistics, Johns Hopkins University, Baltimore, MD 21205, USA ririzarr{at}jhsph.edu
* To whom correspondence should be addressed.
In most microarray technologies, a number of critical steps are required to convert raw intensity measurements into the data relied upon by data analysts, biologists, and clinicians. These data manipulations, referred to as preprocessing, can influence the quality of the ultimate measurements. In the last few years, the high-throughput measurement of gene expression is the most popular application of microarray technology. For this application, various groups have demonstrated that the use of modern statistical methodology can substantially improve accuracy and precision of the gene expression measurements, relative to ad hoc procedures introduced by designers and manufacturers of the technology. Currently, other applications of microarrays are becoming more and more popular. In this paper, we describe a preprocessing methodology for a technology designed for the identification of DNA sequence variants in specific genes or regions of the human genome that are associated with phenotypes of interest such as disease. In particular, we describe a methodology useful for preprocessing Affymetrix single-nucleotide polymorphism chips and obtaining genotype calls with the preprocessed data. We demonstrate how our procedure improves existing approaches using data from 3 relatively large studies including the one in which large numbers of independent calls are available. The proposed methods are implemented in the package oligo available from Bioconductor.
Keywords: Affymetrix; Genotyping; High-throughput; Microarrays
Received June 27, 2006; revised September 18, 2006; accepted for publication October 12, 2006.
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