Discriminant analysis to evaluate clustering of gene expression data.

摘要: Abstract In this work we present a procedure that combines classical statistical methods to assess the confidence of gene clusters identified by hierarchical clustering expression data. This approach was applied publicly released Drosophila metamorphosis data set [White et al., Science 286 (1999) 2179–2184]. We have been able produce reliable classifications groups and genes within applying unsupervised (cluster analysis), dimension reduction (principal component analysis) supervised (linear discriminant in sequential form. provides means select relevant information from microarray data, reducing number require further biological analysis.