M3D: a kernel-based test for spatially correlated changes in methylation profiles.
Bottom Line: We propose a non-parametric, kernel-based method, M(3)D, to detect higher order changes in methylation profiles, such as shape, across pre-defined regions.The test statistic explicitly accounts for differences in coverage levels between samples, thus handling in a principled way a major confounder in the analysis of methylation data.Empirical tests on real and simulated datasets show an increased power compared to established methods, as well as considerable robustness with respect to coverage and replication levels.
Affiliation: IANC, School of Informatics, University of Edinburgh, Edinburgh EH8 9AB and Wellcome Trust Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3JR, UK.Show MeSH
Mentions: Of the 2359 exon regions tested, the M3Ds method identified 689, 676 and 609 with methylation profiles that differed significantly with respect to inter-replicate variation with 4, 3 and 2 replicates in the ESC group, respectively. As is shown in Figure 6, the overlap between the three sets of called regions accounts for almost 90% of the total. Importantly, although the testing lost power with lower replication (as can be expected), only one additional region was called, indicating that the method does not introduce many false positives with reduced replication levels.Fig. 6.
Affiliation: IANC, School of Informatics, University of Edinburgh, Edinburgh EH8 9AB and Wellcome Trust Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3JR, UK.