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Differences in signal magnitude among platforms were nulled out by normalizing the data from each to unit standard deviation.
These data are summarized in Table 3.Positive correlations were also found between chromaticity thresholds and GMFCS scores within groups, indicating that worse motor impairment was associated with worse color discrimination (see Figure 2 for binocular data and Figure 3 for monocular data).The magnitude of color discrimination loss was obtained by normalizing the data from SCP children.
As an alternative way of presenting the data, we also show in the Supplementary figures the individual data points for each donor, adjusted to account for day-to-day variation in assay performance by normalizing the data from each sample to the mean of the control (HbAAαα/αα) cells run on the same day.
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The median was subtracted from each ratio and divided by the standard deviation to center and normalize the data from each array.
Finally, in order to compare the data from different experimental conditions, we calculated 2−ΔΔCt values, which are obtained by normalizing the experimental data by reference data.
These artifacts cannot be eliminated by globally normalizing the data.
By normalizing the cycles we were able to average data from several paddling sequences even when the cycles differed in duration.
Data from Figure 4D were reanalyzed by normalizing the Tyr1-P signals to Rpb1 levels.
To reduce the influence of false positive signals, we normalized the data by dividing signal intensity data from samples (using RNA from engineered cells) with that from negative control parental cells (see Supporting Information for details of the normalization procedure).
ArrayVision software read the slides and normalized the data by subtracting background intensity from the spot intensity values.
To be able to compare the results from different years we have normalized the data by the number of volcanoes.
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