CARMAweb: comprehensive R- and bioconductor-based web service for microarray data analysis
Open Access
- 1 July 2006
- journal article
- Published by Oxford University Press (OUP) in Nucleic Acids Research
- Vol. 34 (Web Server) , W498-W503
- https://doi.org/10.1093/nar/gkl038
Abstract
CARMAweb (Comprehensive R-based Microarray Analysis web service) is a web application designed for the analysis of microarray data. CARMAweb performs data preprocessing (background correction, quality control and normalization), detection of differentially expressed genes, cluster analysis, dimension reduction and visualization, classification, and Gene Ontology-term analysis. This web application accepts raw data from a variety of imaging software tools for the most widely used microarray platforms: Affymetrix GeneChips, spotted two-color microarrays and Applied Biosystems (ABI) microarrays. R and packages from the Bioconductor project are used as an analytical engine in combination with the R function Sweave, which allows automatic generation of analysis reports. These report files contain all R commands used to perform the analysis and guarantee therefore a maximum transparency and reproducibility for each analysis. The web application is implemented in Java based on the latest J2EE (Java 2 Enterprise Edition) software technology. CARMAweb is freely available at https://carmaweb.genome.tugraz.at.Keywords
This publication has 26 references indexed in Scilit:
- Bioconductor: open software development for computational biology and bioinformaticsGenome Biology, 2004
- A comparison of normalization methods for high density oligonucleotide array data based on variance and biasBioinformatics, 2003
- ArrayExpress--a public repository for microarray gene expression data at the EBINucleic Acids Research, 2003
- Variance stabilization applied to microarray data calibration and to the quantification of differential expressionBioinformatics, 2002
- Genesis: cluster analysis of microarray dataBioinformatics, 2002
- Correspondence analysis applied to microarray dataProceedings of the National Academy of Sciences, 2001
- Principal component analysis for clustering gene expression dataBioinformatics, 2001
- Creating the Gene Ontology Resource: Design and ImplementationGenome Research, 2001
- Knowledge-based analysis of microarray gene expression data by using support vector machinesProceedings of the National Academy of Sciences, 2000
- Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA MicroarrayScience, 1995