title: Working with Oligonucleotide Arrays.
abstract: Preprocessing microarray data consists of a number of statistical procedures that convert the observed intensities into quantities that represent biological events of interest, like gene expression and allele-specific abundances. Here, we present a summary of the theory behind microarray data preprocessing for expression, whole transcriptome and SNP designs and focus on the computational protocol used to obtain processed data that will be used on downstream analyses. We describe the main features of the oligo Bioconductor package, an application designed to support oligonucleotide microarrays using the R statistical environment and the infrastructure provided by Bioconductor, allowing the researcher to handle probe-level data and interface with advanced statistical tools under a simplified framework. We demonstrate the use of the package by preprocessing data originated from three different designs.
authors.affiliation: Brazilian Institute of Neuroscience and Neurotechnology (BRAINN) and Department of Statistics, University of Campinas, Rua Sérgio Buarque de Holanda, 651 - Cidade Universitária, Campinas, São Paulo, Brazil. benilton@unicamp.br.
authors.forename: Benilton S
authors.initials: BS
authors.lastname: Carvalho
mesh_terms: D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D015870:Gene Expression; D020869:Gene Expression Profiling / Q000379:methods; D023281:Genomics / Q000379:methods*; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D020641:Polymorphism, Single Nucleotide; D012984:Software; D059467:Transcriptome
keywords: Genotyping; Normalization; Oligonucleotide microarrays; Preprocessing; Probe-level data