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We applied a high stringency data selection, keeping only microarray elements for which at least 80% of the measurements within a set of experiments had fluorescence intensity in both channels at least 3-fold over background intensity.
On the basis of pulsed-temperature cycling and the specific results reported here, we are also exploring a more general question of the trade-off between number of microarray elements and the nature and complexity of transient-driven and temperature-enriching temperature programming for their effects on the performance characteristics of e-noses.
A mixed model ANOVA analysis of the data revealed that 2524.3.3%) of the microarray elements were differentially expressed in response to ConA and the sensitivity of this experiment was calculated to be 80 transcripts per million by the method described in Reverter et al. (2005) [ 31].
This amounted to less than 0.3% of the analyzed microarray elements, and less than one half of the number changed due to the other staining methods tested.
(b) Tabular list of microarray elements mapped onto the example gene IDs when selecting Affymetrix platform.
bNumber of microarray elements selected for sequencing based on cadmium response determined in the current study; Eads et al., in review; and Colbourne et al., in review.
aNumber of microarray elements determined to be significant on the array using the empirical Bayes method to shrink the gene-wise error estimate in cadmium treated vs. control Daphnia pulex (P < 0.05).
The ability of the OPLS model to approximate the expression profile of a microarray elements based only on the weather parameters will be denoted the predicted variation for that particular element.
This is shown in Figure 5 for a set of selected microarray elements.
See Figure 4 for an overview of the microarray elements and the relation to the weather parameters.
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