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We made the model probabilistic by applying a relevant distribution for each variable in the model.
We could directly predict a relevant distribution and dynamics of telomere length from the protein-counting mechanism.
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In a general way, we will write: (5) Σ ∼ π where π represents any relevant distribution with parameters ξ.
Statistical significance was assessed by the Kolmogorov Smirnov test; all relevant distribution shifts are statistically significant; p-values are shown for relevant comparisons in Figure 2 figure supplement 1F.
Given the relevant distribution parameters, a set of random samples is returned, corresponding to the probability of each possible outcome (with the total summing to 1).
The studies in the meta-analysis were assumed to be a random sample of the relevant distribution of effects, and the combined effect estimated the mean effect of these different subpopulation means.
The variance of the marker effects (σ gi ) was estimated for every marker using a relevant prior distribution, which was a mixture of an inverted chi-squared distribution and a discrete probability mass at σgi = 0.
The 'BayesB' model is described in more detail in earlier papers [ 3] and [ 8], but briefly, the variance of the marker effects (σgi) was estimated for every marker using a relevant prior distribution which was a mixture of an inverted chi-squared distribution and a discrete probability mass at σgi = 0.
We estimated the significance of this overlap using a random model (see Methods) to generate a relevant background distribution that takes into account also the real dependences between the pathways and biological processes.
To estimate the significance of the fact that a biological process passed this criterion in a way that corrects for multiple testing, we devised a random model to generate a relevant background distribution, which takes into account the real dependences between the pathways and biological processes.
Using Bayesian statistics, we will include prior knowledge in the analysis by specifying a relevant prior distribution.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com