We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Discriminant analysis to evaluate clustering of gene expression data
- Authors
Méndez, Marco A.; Hödar, Christian; Vulpe, Chris; González, Mauricio; Cambiazo, Verónica
- Abstract
In this work we present a procedure that combines classical statistical methods to assess the confidence of gene clusters identified by hierarchical clustering of expression data. This approach was applied to a publicly released Drosophila metamorphosis data set [White et al., Science 286 (1999) 2179–2184]. We have been able to produce reliable classifications of gene groups and genes within the groups by applying unsupervised (cluster analysis), dimension reduction (principal component analysis) and supervised methods (linear discriminant analysis) in a sequential form. This procedure provides a means to select relevant information from microarray data, reducing the number of genes and clusters that require further biological analysis.
- Subjects
GENE expression; DISCRIMINANT analysis; CLUSTER analysis (Statistics); PRINCIPAL components analysis
- Publication
FEBS Letters, 2002, Vol 522, Issue 1-3, p24
- ISSN
0014-5793
- Publication type
Article
- DOI
10.1016/S0014-5793(02)02873-9