In order to determine whether measured mRNA levels or other global data
are consistent with a particular model of a cellular process, we need
to have some notion of how much measurement error and biological
variation can influence the measurements. Accordingly, we have
developed refined statistical procedures, based on maximum-likelihood
estimation, to determine which changes observed with a DNA microarray
are significant and which are likely due to error. These methods are
available for download (Windows, Linux, and SunOS platforms) through
the public-domain software package VERA and SAM.
VERA estimates the parameters of a statistical model that describes
multiplicative and additive errors influencing an array
experiment, using the method of maximum likelihood. SAM gives a value,
lambda, for each gene on an array, which describes how likely it is
that the gene is expressed differently between the two cell
populations. A large value of lambda means that the gene is almost
certainly expressed differentially, while a small value (close to 0)
indicates that there is no evidence for differential expression.
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