It has been reported that one of the problems of looking for enrichment of functional themes using 450k data is the bias introduced by the differing number of probes per gene. (See Geeleher et al, http://www.ncbi.nlm.nih.gov/pubmed/23732277)
The paper linked above describes correcting for this bias by adopting the probability-weighting function (pwf) in the package goseq, that is more usually used to correct for gene-length bias in RNA-seq data.
It is straightforward to use this probability weighting function to integrate with downstream gene ontology / KEGG enrichment analysis, but it is not obvious to me how you can adjust the p values from a 450k analysis of different groups using this method and then apply to an external process like Ingenuity Pathway Analysis.
Is there a code snippet that I could use or could help me understand how to use the pwf to adjust 450k p values in this way?