A web-based tool for principal component and significance analysis of microarray data

• DOI: 10.1093/bioinformatics/bti343
• Publication Date: 2005-02-26T01:13:42Z
• Authors: A. A. Sharov; D. B. Dudekula; M. S. H. Ko
• Keywords: Gene chip analysis; Biplot

We have developed a program for microarray data analysis, which features the false discovery rate testing statistical significance and principal component analysis using singular value decomposition method detecting global trends of gene-expression patterns. Additional include variance with multiple methods error adjustment, correction cross-channel correlation two-color microarrays, identification genes specific to each cluster tissue samples, biplot tissues corresponding tissue-specific genes, clustering that are correlated (PC), three-dimensional graphics based on virtual reality modeling language sharing PC between different experiments. The software also supports parameter gene search graphical output results. is implemented as web tool thus speed does not depend power client computer.The can be used on-line or downloaded at http://lgsun.grc.nia.nih.gov/ANOVA/