Lumi

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lumi
Latest release: 2.0 / March 4, 2007
OS: Linux, UNIX, Mac OS X, Windows
Platform: R programming language and Bioconductor
Use: Analysis of Illumina microarrays
License: GNU General Public License
Website: www.basic.northwestern.edu/projects/lumi/

lumi is a free, open source and open development software project for the analysis and comprehension of Illumina microarray data. The project was started in the summer of 2006 and set out to provide algorithms and data management tools of Illumina in the framework of Bioconductor. It is based on the statistical R programming language.

Contents

[edit] Features

The lumi package provides an analysis pipeline for probe-level Illumina data, including probe-identifier management (nuID), quarterly updated probe-to-gene mapping and annotation using the latest release of RefSeq (nuIDblast), probe-intensity transformation (VST) and normalization (RSN), and quality control (QA/QC). By extending the ExprSet object with Illumina-specific features, Lumi is designed to work with other Bioconductor packages, such as Limma and GOstats to detect differential genes and conduct Gene Ontology analysis.

[edit] History

The "lumi" project was started in the summer of 2006 at the Bioinformatics Core Facility of the Robert H. Lurie Comprehensive Cancer Center, Northwestern University. The project team consists of Drs. Pan Du, Simon M. Lin, and Warren A. Kibbe. The project was started upon a request for collaboration from Dr. Serdar E. Bulun to analyze a set of new Illumina microarray data acquired at his lab on the study of the effect of retinoic acids on cancers. Dr. Pan Du led the software development of the project. Lumi was the first software package to utilize the unique design of redundancy of beadArrays for the data transformation and normalization processes. The first release of lumi was on January, 3, 2007 through the Bioconductor website. Before its formal release, it was beta-tested at Norwegian Radiumhospital, Leiden University Medical Center, Universiteit van Amsterdam, Università degli Studi di Brescia, UC Davis, Wayne State University, NIH, M.D. Anderson Cancer Center, Case Western Reserve University, Harvard University, Washington University, and Walter and Eliza Hall Institute of Medical Research.

[edit] See also

  • Bioconductor, integrated software for the statistical analysis of wet lab data in molecular biology

[edit] External links


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