The normalization strategy was tested by comparing RT-qPCR data of both normalized and raw expression levels of brain natriuretic peptide precursor (NPPB), a gene known to be up-regulated in heart failure.
SCS = Standard Curve Slope The most stable pair of reference gene primers were selected using the normalization strategy proposed by [ 33].
But the expression patterns of the most differentially regulated genes (validated independently by real-time PCR, see Figure 3) were independent from the normalization strategy (data not shown).
A detailed analysis for selected targets comparing this normalization strategy with the one recommended by Luminex™ (based on the spike-in controls) showed that for individual microRNAs expression patterns depend on the normalization strategy.
For the BP ontology, the normalization strategy using the GO-universal idea (Nunivers strategy) outperforms other normalization techniques by consistently showing one of the highest correlations with sequence, Pfam and EC similarity, except for resolution, where the strategy of using the highest IC value (Nmax strategy) performs better.
For the MF ontology, the normalization strategy using the Nunivers strategy produces lower Pearson's correlation with PFAM and sequence similarity compared to the other normalization strategies, but overall, it outperforms them in terms of EC similarity.
In this chapter, we will underscore how to design experiments in order to be able to answer questions posed by the investigator, the different normalization strategies used and their assumptions, the different types of statistical analysis and adjustments for multiple testing, methods of uncovering patterns in the data, and strategies to find meaning in the results.
Note that we do not aim at comparing the performance of the peak-callers to each other, but rather the performance of each peak-caller depending on which background model that was in use or if the input data had been pre-processed by our normalization strategy or not.
Applying the same normalization strategy, both datasets were jointly and independently normalized to study the influence of the normalization to the final results.
