Introduction to myoRDNA
Introduction | Package functionality | Installation | Overview of the analytical workflow | Loading your data into myoRDNA | Step 1: Load the example methylation dataset | Step 2: Define experimental conditions | Step 3: Construct a methylRawList object | Step 4: Extract rDNA methylation data | Step 5: Adjust rDNA genomic coordinates | rDNA copy-number analysis | Absolute rDNA copy number | Calculating absolute copy number | Relative rDNA copy number | Calculating relative copy number | Considerations for copy-number estimation | Regional rDNA methylation analysis | Step 1: Partition rDNA into genomic regions | rDNA regions | Step 2: Calculate aggregate methylation metrics | Mathematical formulation of methylation proportions | Mean methylation proportion | Median methylation proportion | Differential rDNA methylation analysis | Statistical methodology | Binomial logistic regression | $$\operatorname{logit}(p_i) | \log\left(\frac{p_i}{1-p_i}\right) | $$\operatorname{Var}(Y_i) | Quasi-binomial logistic regression | $$\boxed{\operatorname{Var}(Y_i) | $$\widehat | Beta-binomial logistic regression | Step 1: Site-level differential methylation | Step 2: Region-level differential methylation | $$M_ | $$U_ | Step 3: Interpreting differential methylation | $$\widehat | $$\widehat | $$\boxed | 100\left(\widehat | Step 4: Multiple-testing correction | Beta-binomial optimisation and model diagnostics | Available optimisation algorithms | Assessing model convergence | Session information
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