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Sensory transformations and the use of multiple reference frames for reach planning.
It then extends conventional motion prediction methods through sub-pixel estimation and the use of multiple reference frames.
This chapter illustrates the use of multiple reference frames (MRF) to model the three-dimensional flow field in a stirred tank agitated with Rushton turbines and pitched-blade turbines.
Enhanced inter prediction features include the use of multiple reference frames, variable block-size motion compensation, and quarter-pixel precision.
Although the use of multiple reference genes is recommended by several reports [ 13, 14], we chose a single reference gene for this case because the use of multiple reference genes would increase variations in measurement.
While the relative gene stability rankings may vary subtly depending on which algorithm is applied [ 41, 49, 50], use of multiple reference genes provides a considerably more robust result compared with relying on a single RNA transcript [ 5].
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A recent published method, FishingCNV, tried to address the second limitation by using the average of multiple reference samples as the denominators in log-ratio calculation, but did not address the regional noises in individual samples (the numerator), which led to false CNV calls (details in Supplementary Section S2.3).
In order to minimise the risk of bias from using a single gene as a reference, it is preferable to normalize using the geometric mean of multiple reference genes, as it was proposed previously [ 33].
As mentioned before, expression results are considerably more reliable if they are normalized using the geometric mean of multiple reference genes [ 24].
We conclude that analysis and averaging of multiple reference genes using a GeNorm approach gives a more reliable estimate of total cfDNA quantity.
The negative correlation remained present (r = −0.83) when the geometric mean of multiple reference genes (instead of individual reference genes) was used.
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