Expression Data Analysis

S-Score: The "significance-score" algorithm (S-score) was developed in our laboratory by Dr. Li Zhang. This produces a score for a comparison of the expression of a gene between two samples (e.g. control and "treated"). The S-score produces a robust measure of expression changes by weighting oligonucleotide pairs according to their signal strength above empirically determined noise levels. The procedure produces scores centered around "0" (no change) with a standard deviation of 1. Thus, scores >2 or <-2 from a single comparison have, on average, a 95% chance of being "real changes" in terms of the chip hybridization. This does not, however, imply that they are biologically reproducible.

S-score Software: A program that will calculate S-scores using Affymetrix *.CEL and *.CDF files, is available. A Windows version can be downloaded.

PDNN: Also developed by Dr. Li Zhang, the position-dependent-nearest-neighbor (PDNN) model uses a simple free energy model for the formation of RNA-DNA duplexes on short oligonucleotide arrays. PDNN assigns a different weight factor for each position on the probe and models both gene-specific and non-specific modes of binding. For further information, please click here.