The oligo package is a comprehensive solution for preprocessing oligonucleotide microarray data, developed to address the limitations of existing tools. It is based on BioConductor principles of transparency, reproducibility, and efficiency. The package supports a wide range of microarray applications, including gene expression, SNP arrays, exon arrays, and tiling arrays. It provides a unified framework for preprocessing data and interfaces with other BioConductor tools for downstream analysis. The package is freely available through BioConductor and supports data from Affymetrix and NimbleGen arrays. The oligo package includes structures to simplify data handling and interaction with other packages. It distinguishes between feature-level, summarized, and annotation data, using S4 classes. Annotation packages are required for data processing, and manufacturers provide annotation files for different array types. The package supports raw data files and annotation files, which are used to create annotation packages. The package manages raw intensities using multiple classes, allowing differentiation between data from different applications. The package is tightly integrated with other BioConductor tools, enabling efficient data analysis and visualization. It supports preprocessing of gene expression data using RMA, genotype calling from SNP arrays using CRLMM, and preprocessing of exon arrays at exon and transcript levels. It also interfaces with ACME to find enriched regions using tiling arrays. The oligo package provides a flexible and efficient framework for handling various microarray data types, improving the consistency and productivity of data analysis within the BioConductor project. It supports multiple vendors and platforms, efficient storage and access schemes for high-throughput arrays, and native support for manufacturer files. The package allows handling data from different applications and manufacturers, using their native file schemes, avoiding potential issues from conversion tools. It serves as an interface between data files and methodologies implemented by other BioConductor packages, defining a unified framework for efficient use of R and BioConductor environments.The oligo package is a comprehensive solution for preprocessing oligonucleotide microarray data, developed to address the limitations of existing tools. It is based on BioConductor principles of transparency, reproducibility, and efficiency. The package supports a wide range of microarray applications, including gene expression, SNP arrays, exon arrays, and tiling arrays. It provides a unified framework for preprocessing data and interfaces with other BioConductor tools for downstream analysis. The package is freely available through BioConductor and supports data from Affymetrix and NimbleGen arrays. The oligo package includes structures to simplify data handling and interaction with other packages. It distinguishes between feature-level, summarized, and annotation data, using S4 classes. Annotation packages are required for data processing, and manufacturers provide annotation files for different array types. The package supports raw data files and annotation files, which are used to create annotation packages. The package manages raw intensities using multiple classes, allowing differentiation between data from different applications. The package is tightly integrated with other BioConductor tools, enabling efficient data analysis and visualization. It supports preprocessing of gene expression data using RMA, genotype calling from SNP arrays using CRLMM, and preprocessing of exon arrays at exon and transcript levels. It also interfaces with ACME to find enriched regions using tiling arrays. The oligo package provides a flexible and efficient framework for handling various microarray data types, improving the consistency and productivity of data analysis within the BioConductor project. It supports multiple vendors and platforms, efficient storage and access schemes for high-throughput arrays, and native support for manufacturer files. The package allows handling data from different applications and manufacturers, using their native file schemes, avoiding potential issues from conversion tools. It serves as an interface between data files and methodologies implemented by other BioConductor packages, defining a unified framework for efficient use of R and BioConductor environments.