Statistical analysis
Differential methylation was investigated probe-wise using linear models with empirical Bayes variance correction as implemented in the For each contrast in each model, the number and identity (where applicable) of any differentially methylated probes (DMPs) were obtained. For detection of DMPs, The findings from different data-processing choices were then compared along five dimensions:Number and identity of differentially methylated probes (DMPs); for infant sex, the direction of differential methylation (‘down’, corresponding to negative t-statistics or lower methylation in females, Consistency of rankings by Consistency of rankings by logFC for ‘top 10’ probes, as well as the consistency of the logFC estimates. This gives an indication of whether the estimates of effect are similar between methods.Overall distribution of Overall distribution of logFC estimates. Under the null hypothesis of no effect, logFC estimates should be roughly normally distributed around 0. If effects are present, there will be more estimates far away from 0 (with the direction depending on whether the effect is one of hypomethylation or hypermethylation, and the distance depending on the strength of the effect).