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

We have developed a program for microarray data analysis, which features the false discovery rate for testing statistical significance and the principal component analysis using the singular value decomposition method for detecting the global trends of gene-expression patterns. Additional features i...

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Vydáno v:Bioinformatics Ročník 21; číslo 10; s. 2548 - 2549
Hlavní autoři: Sharov, Alexei A., Dudekula, Dawood B., Ko, Minoru S. H.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford Oxford University Press 15.05.2005
Oxford Publishing Limited (England)
Témata:
Algorithms
Biological and medical sciences
Computer Graphics
Computer Simulation
Fundamental and applied biological sciences. Psychology
Gene Expression Profiling - methods
General aspects
Internet
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Models, Biological
Models, Statistical
Oligonucleotide Array Sequence Analysis - methods
Principal Component Analysis
Principal components analysis
Software
User-Computer Interface
Variance analysis
Data analysis
Multiple
Analysis method
Detection
Gene expression
Microarray
Variance analysis
Principal component analysis
Singular value decomposition
ISSN:1367-4803, 1460-2059, 1367-4811
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Popis
Shrnutí:We have developed a program for microarray data analysis, which features the false discovery rate for testing statistical significance and the principal component analysis using the singular value decomposition method for detecting the global trends of gene-expression patterns. Additional features include analysis of variance with multiple methods for error variance adjustment, correction of cross-channel correlation for two-color microarrays, identification of genes specific to each cluster of tissue samples, biplot of tissues and corresponding tissue-specific genes, clustering of genes that are correlated with each principal component (PC), three-dimensional graphics based on virtual reality modeling language and sharing of PC between different experiments. The software also supports parameter adjustment, gene search and graphical output of results. The software is implemented as a web tool and thus the speed of analysis does not depend on the power of a client computer. Availability: The tool can be used on-line or downloaded at http://lgsun.grc.nia.nih.gov/ANOVA/ Contact: kom@mail.nih.gov
Bibliografie:To whom correspondence should be addressed.
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ISSN:1367-4803
1460-2059
1367-4811
DOI:10.1093/bioinformatics/bti343