Effect of normalisation method
Normalisation method had a substantial influence on number and identity of DMPs, rankings of probes and There was a fair degree of consistency in rankings of probes by Distributions of Overall, there was little difference between SQN and SWAN methods when adjusting for batch in the model. There is some evidence that SQN would result in fewer significant DMPs than SWAN for known effects (particularly when using supervised ComBat), but (many) more spuriously significant DMPs than either SWAN or BMIQ where effects are absent. The behaviour of BMIQ was more variable depending on other dimensions of the pipeline, but had a wider dispersion of logFC estimates than the other methods, particularly when adjusting for batch in the model. This tended to result in more DMPs in some scenarios, but in general will lead effect estimates derived from BMIQ data to be more extreme (and probably overestimates of the true effect).