We see that \(x\) is very predictive of \(y\), as we expect. # Residual deviance: 39.537 on 48 degrees of freedom # Null deviance: 53.720 on 49 degrees of freedom # (Dispersion parameter for binomial family taken to be 1) In terms of DNA methylation at a particular loci, this would be 50 samples (25 in each group), each with coverage 10, where there’s a 20% methylation difference between the two groups. We’ll sample 50 draws from a binomial distribution, each with \(n=10\). Let the probability of success equal \(p=(1-x)p_0 + xp_1\), so that Let’s start with a very simple example, where we have two groups (goverened by \(x\)), each with a different probability of success.
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