System and method for parameter estimation in biological processes
A biological process and parameter technology, applied in biochemical equipment and methods, biostatistics, microbial measurement/inspection, etc., can solve the problem that methylation measurement results do not have normal distribution or Gaussian distribution errors, etc.
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Embodiment 1
[0069] To illustrate the application of the theory presented above, more than 40 samples were randomly drawn from the 1440 deviations measured by repeated measurements of the same tissues described above. A constant value of 0.55 was added to 20 samples and assigned treatment H, while a constant value of 0.45 was added to the other 20 samples and assigned treatment L. A uniform random variable sampled between 0 and 0.1 is added to each value to simulate inter-individual variation.
[0070] Analysis of variance was performed on this simulated data set using the maximum likelihood method derived above and the state-of-the-art least squares technique. The least squares estimates were not significantly different (P<0.22), with estimates of H=0.55±0.10 and L=0.46±0.10. However, the maximum likelihood estimate was highly significant (P<0.01), with estimates of H=0.55±0.04 and L=0.45±0.04.
[0071] Since this simulation example has a difference between the H and L performed specifi...
Embodiment 2
[0072] Example 2: Application of Estimating the Effect of Parity on the Promoter Methylation of the H19 Gene
[0073] The ratio of CpG methylation at 13 CpG sites in the promoter of the H19 gene measured on the subjects' marrow samples described in the Materials and Methods section was analyzed to determine parity by means of maximum likelihood using the method described above sexual influence.
[0074] The frequency distribution of methylation measurements at each CpG site showed a high degree of non-normality, all with skewed tails, with high bias at low frequencies. figure 2 An example of CpG(2) is shown in . In these cases the "usual" ANOVA least squares procedure would be expected to perform poorly, and the inferences would be unreliable. Taking a logarithmic transformation did not improve the situation, probably because the form of the tail of the methylation distribution falls faster than the exponential form.
[0075] The effect of parity on the estimates of the pr...
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