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The BeadChip microarrays were normalized using a cubic-spline normalization algorithm using Illumina's BeadStudio software in an attempt to minimize environmental factors during microarray processing that may affect levels of expression.
Normalization of the final set of microarrays proceeded by computing log ratios of the bound (Cy5) and input (Cy3) microarray channel intensities for each microarray and then microarrays were normalized to one another using quantile normalization under the assumption that all samples have identical overall methylation levels.
The detailed information for qPCR efficiency and% relative RNA abundance of the measured genes is provided in Suppl 1. Table 4. Data from a total of 12 microarrays were normalized for dye and microarray effects (ie, Lowess normalization and microarray centering) and used for statistical analysis.
Microarrays were normalized using the MAS5 algorithm, and expression threshold and ceiling values were applied as described [8].
Signal intensity values from microarrays were normalized and converted to fold-change values as previously described [13].
Signal intensities across all microarrays were normalized using the quantile-quantile method (www.bioconductor.org) to provide consistency of signal strength across developmental and dietary conditions.
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The median microarray intensity for all microarrays was normalized to 100, and probe sets with median intensities >100 were scored.
Briefly, this method finds the microarray with the overall median Cy3 signal for use as a baseline microarray (here 12 hpf, replicate C) to which all other microarrays are normalized.
To identify the specific RNAs that were associated with each candidate RBP, the Log2 ratios from each microarray were normalized to the average of the Mock arrays (the average of the Mock arrays was calculated after median normalization).
Raw data derived by oligo microarray were normalized using lowess algorithm exploiting MIDAW web tool [ 19].
Signal intensities for an entire microarray were normalized to the 50% percentile median value.
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