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Data have been normalized using a reference gene; (D and E) The expression of pluripotent genes in the four treatment groups described in the text; (F H) The expression of differential genes in the four treatment groups described in the text.
In this work, the images have been normalized using a general affine model, with 12 parameters ([ 20- 22]).
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To minimize the effect of variation from non-biological factors, the values of each sample were normalized using a quantile normalization method.
For each dataset the height of the returns was normalized using a digital elevation model (DEM) provided along with the datasets.
Concentrations of dsRNAs targeting the various Trp channels were normalized using a UV spectrophotometer.
For use in principle component analysis (PCA), the peak areas were normalized using a Z-transformation, to reduce the "closure" effect [i.e. the relative contribution of one peak affecting the relative contribution of the rest of the compounds; ref. 48].
Raw data from these screens were normalized using a standard plate-based Z-score analysis.
The average clutch length was normalized using a Box-Cox transformation.
The amount of PCR products was normalized using a housekeeping gene (β-actin or GAPDH) to calculate the relative expression ratios.
To make the inter-slide signals more comparable, all net signals of scanned points were normalized using a global-mean method.
For reduction of signal bias due to, e.g., spatial variation in coil sensitivity profiles, the images were normalized using a prescan and a weak intensity filter was applied as implemented by the scanner's manufacturer.
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