Robust singular value decomposition analysis of microarray data.

ABSTRACT: In microarray data there are a number of biological samples, each assessed for the level of gene expression for a typically large number of genes. There is a need to examine these data with statistical techniques to help discern possible patterns in the data. Our technique applies a combination of mathematical and statistical methods to progressively take the data set apart so that different aspects can be examined for both general patterns and very specific effects. Unfortunately, these data tables are often corrupted with extreme values (outliers), missing values, and non-normal distributions that preclude standard analysis. We develop a robust analysis method to address these problems. The benefits of this robust analysis will be both the understanding of large-scale shifts in gene effe

SUBMITTER: Liu L 

PROVIDER: S-EPMC263735 | biostudies-literature | 2003 Nov

REPOSITORIES: biostudies-literature