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Second, according to the compaction displacement, we calculated the corresponding porosity value of each data point.
The numeric value of each data object is updated as the monitoring window slides.
Third, according to the relationship between viscosity and temperature, we corrected the corresponding permeability value of each data point.
Specifically, we adopt a local linear regression model to predict the label value of each data point in a local patch.
Each data stream contains a sequence of data objects associated with numeric values, and the aggregate numeric value of each data object is calculated from distributed data streams.
We weighted the y value of each data point by its respective study sample size (w) and then calculated the weighted median ((widetilde{{wy}}_{i})) for each bin (i) as a measure of weighted central tendency.
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Each element in the AF matrix contains the sim u, v) value of each data-point pair, and (AFin [0,2]^{ntimes n}).
The values of each data set are in the Additional file 1: Table S1.
The weights of all data points were set equal after flattening square values of each data point.
Absolute expression values of each data set were converted to the logarithmic scale and normalized so that the mean is equal to 0 and the variance is equal to 1 in each sample.
Briefly, expression values were Log2 transformed and processed by subtracting the mean value for each gene across all samples of the compendium from all data points, so that in all cases expression values of each data point were reported as positive or negative depending on whether it was higher or lower than the mean value of that gene across the samples.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com