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To determine inter-individual variation we calculated the mean sum of squares for all CpG sites and selected the CpGs with a mean sum of squares >0.025.
The cut-off we used for the effect size was a 20% difference in DNA methylation between two tissues, which equals a ≥10% difference from the overall mean (≥10% difference equals a mean sum of squares ≥0.01 since the square of 10% = 0.1).
Although tissue-differences were the main driver of variation in DNA methylation, we observed inter-individual variation for 15,803, 11,719, 46,437 and 8,415 CpGs in the liver, subcutaneous fat, omentum and skeletal muscle, respectively (defined as a mean sum of squares > 0.025).
tDMPs were defined as CpGs with a DNA methylation difference between tissues that was: (1) genome-wide significant (P < 10-7) and (2) had a mean sum of squares ≥ 0.01 (equals (10%), that is, the mean of the difference between the individual tissues and the overall mean across tissues should be greater than 10%).
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The Somalis scored a mean sum score of 21.17 (SD = 16.19) on the PDS while the Rwandese had a mean sum score of 10.05 (SD = 9.7).
More specifically, a local, window-based disparity matching [13] using a ZSAD (zero mean sum of absolute differences) cost function is employed.
- pF: The pF is intended to capture the tightness of clusters, and is a ratio of the mean sum of squares between groups to the mean sum of squares within groups.
The result shows that the Levenberg Marquardt approximation algorithm is the preferred method, as this algorithm reduces the root of the mean sum of squared (RMS) error to a significantly small value.
The mean number of splits and the mean sum of lengths of splits between a sequence and the NSI/CCR5-tropic sequences on the tree are used as the score predictive of the coreceptor usage.
The mean sum of total As excreted in urine, assuming an excretion rate of 1.5 L/day, was 191 μg/day.
Mean sum of squares.
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