Provides class infrastructure and associated methods to construct an Illumina analysis workflow pipeline starting with raw data through functional analysis. Besides supporting the existing algorithms for microarray data, the lumi package includes several unique parts: (i) a variance-stabilizing transformation that utilizes the technical replicates available on the Illumina microarray; (ii) normalization algorithms designed for Illumina microarray data and; iii) the nucleotide universal identifier annotation packages.
A package that extends and improves the functionality of the base affy package. Routines that make heavy use of compiled code for speed. Central focus is on implementation of methods for fitting probe-level models and tools using these models.
Implements a unified framework for preprocessing microarray data and interfaces with other BioConductor tools for downstream analysis. The Oligo package provides array coordinates, feature types, sequences, feature names and other relevant information for preprocessing. Developers can use oligo solutions to facilitate the integration of their tools with BioConductor. They also benefit from the unified model that the package makes available, as the consistency in data delivery and handling improves efficiency.
An open-source, web-based, suite for the analysis of gene expression and aCGH data. Asterias implements validated statistical methods, and most of the applications use parallel computing, which permits taking advantage of multicore CPUs and computing clusters. Access to, and further analysis of, additional biological information and annotations (PubMed references, Gene Ontology terms, KEGG and Reactome pathways) are available either for individual genes (from clickable links in tables and figures) or sets of genes. These applications cover from array normalization to imputation and preprocessing, differential gene expression analysis, class and survival prediction and aCGH analysis.
Identifies features correlating with a phenotype of interest in the presence of potential confounding factors. Using simulated data, we show that ISVA performs well in identifying confounders as well as outperforming methods which do not adjust for confounding. Using four large-scale Illumina Infinium DNA methylation datasets subject to low signal to noise ratios and substantial confounding by beadchip effects and variable bisulfite conversion efficiency, we show that ISVA improves the identifiability of confounders and that this enables a framework for feature selection that is more robust to model misspecification and heterogeneous phenotypes. Finally, we demonstrate similar improvements of ISVA across four mRNA expression datasets. Thus, ISVA should be useful as a feature selection tool in studies that are subject to confounding.
Performs high-throughput expression analysis, with accurate and consistent results. Codelink is a single-channel microarray platform that uses 30-bp oligonucleotide probes designed for three different organisms; human, mouse and rat. It facilitates reading, preprocessing and manipulating Codelink microarray data. The raw data must be exported as text file using the software. The tool provides users with an easy to use interface for the analysis of data on the R platform.