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The volume of a pillar can then be simply estimated as the area of the grid multiplied by the intensity of the data points corresponding to that grid.
In order to adapt differing total intensities between measurements at different times, the intensity data of each data set was normalized by the total intensity of the data set.
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Considering the weak average intensities of the data sets, the Rmerge of ∼10% is very acceptable.
As in other tiling array data, the probe intensities of the data, which were supposed to represent the same transcript unit, were highly varied due to the heterogeneous probe affinity (Figure 3A) [27].
In the second approach, only intensities which were in the upper 20% of the intensity range of the data were taken into account.
In the past it changed intensity of half the data sets uniformly while in the pattern recognition method it influences a fit applied independently to each single molecule intensity pattern.
Such multi-look averaging modifies the intensity distribution of the data and subsequent statistical modelling must take this into account for parameter estimation or statistical inference.
Because the p95 value represents a measure of the fluorescence intensity distribution of the data, a low p95 (p95<2500) corresponds to poor-quality hybridizations.
For any segmentation algorithm, it is important that the intensity ranges of the data are consistent.
We started by creating a maximum intensity projection of the data.
Therefore, the data matrix was multiplied by a factor of 0.333 in order to reflect the mean intensity value of the data used to generate our GEPR (500).
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