Empirical validation of the S-Score algorithm in the analysis of gene expression data.

ABSTRACT:

Background

Current methods of analyzing Affymetrix GeneChip microarray data require the estimation of probe set expression summaries, followed by application of statistical tests to determine which genes are differentially expressed. The S-Score algorithm described by Zhang and colleagues is an alternative method that allows tests of hypotheses directly from probe level data. It is based on an error model in which the detected signal is proportional to the probe pair signal for highly expressed genes, but approaches a background level (rather than 0) for genes with low levels of expression. This model is used to calculate relative change in probe pair intensities that converts probe signals into multiple measurements with equalized errors, which are summed over a probe set to form

SUBMITTER: Kennedy RE 

PROVIDER: S-EPMC1550434 | biostudies-literature | 2006 Mar

REPOSITORIES: biostudies-literature