@ARTICLE{Carvalho2006,
  author = {Benilton Carvalho and Henrik Bengtsson and Terence P Speed and Rafael
	A Irizarry},
  title = {Exploration, Normalization, and Genotype Calls of High Density Oligonucleotide
	SNP Array Data.},
  journal = {Biostatistics},
  year = {2006},
  month = {Dec},
  abstract = {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 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 methodology useful for preprocessing Affymetrix
	SNP chips and obtaining genotype calls with the preprocessed data.
	We demonstrate how our procedure improves existing approaches using
	data from three relatively large studies including one in which large
	numbers of independent calls are available. The proposed methods
	are implemented in the package oligo available from Bioconductor.},
  doi = {10.1093/biostatistics/kxl042},
  keywords = {genotyping},
  owner = {bcarvalh},
  pii = {kxl042},
  pmid = {17189563},
  timestamp = {2007.02.28},
  url = {http://dx.doi.org/10.1093/biostatistics/kxl042}
}
