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In recent years, new high-throughput technologies allowed the measuring of expression profiles of thousands genes simultaneously.
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It uses CP values (instead of relative quantities) as input and employs a different measure of expression stability from geNorm and NormFinder.
Since BPND values are often used in quantification of PDE10A as a measure of expression, it is important to also take affinity effects into account when quantifying PDE10A.
We investigated the relationships between our three measures of expression.
Some studies used the Euclidean distance of expression profiles as a measure of expression divergence [5], [28], [29], [30].
The read counts in these two categories were considered a measure of expression pertaining to the specific locus.
We did not use the correlation coefficient as a measure of expression divergence since there are problems with this measure for genes that are uniformly expressed (unpublished results).
Additionally, we used the same experimental design and same samples to generate measures of expression for Affymetrix U133Plus2, thereby allowing an unbiased comparison of the two platforms.
Because 'omics' measures of expression are usually on an arbitrary scale, we chose to evaluate ratios or their equivalent differences on a log scale [15].
Further studies will be necessary to define the biological role of these genes in proteinuric kidney disease and to determine if measures of expression of these genes are predictive of long-term clinical outcome.
Specifically, we compare the measures of expression for HuEx and U133Plus2 arrays to evaluate the precision of these measures as well as the specificity and sensitivity of the measures' ability to detect differential expression.
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