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