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Even after normalization, variation in processing technician, location and time can result in probe-specific batch effects (as reviewed in [ 9]).
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Thus, this normalization introduces variation.
In addition to background correction, normalization of variation within, as well between arrays, needs to be considered in two-colour microarray experiments.
To assess the effect of normalization on variation for data in Figure 7 we calculated IQR for M values of identified populations.
Without a normalization step, variation in the read counts for each index is most likely due to the molar representation of each library in the pool.
The fold-over control (FOC) normalization reduces variation in signals that could potentially arise between probing operations performed at different times.
Relative expression of the GADD45α and BTG2 genes was measured by real-time quantitative RT-PCR using β-actin as internal control for possible contamination of genomic DNA and for normalization of variation in the amounts of PCR product loaded.
In summary, spot area normalization reduces variation in FPI (final population intensity) and AUGC (area under growth curve), while not affecting MSR (maximum specific rate) or TMR calculations (Fig. 4, Tables 1 and 2).
The FA-normalization minimizes variation due to TA changes.
Rad mRNA level was assessed by real-time quantitative RT-PCR as previously described [7] and 18S level was measured for normalization of variations in RNA input and cDNA synthesis.
Such normalization accounted for variation in reaction yield seen from day to day, possibly due to enzyme variation during storage.
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