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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Bibliographic Details
Published in:	Bioinformatics Vol. 21; no. 10; pp. 2548 - 2549
Main Authors:	Sharov, Alexei A., Dudekula, Dawood B., Ko, Minoru S. H.
Format:	Journal Article
Language:	English
Published:	Oxford Oxford University Press 15.05.2005 Oxford Publishing Limited (England)
Subjects:	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
Online Access:	Get full text
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