Differential Methylation

Introduction: Differential Methylation of Sample Groups

Differential methylation analysis was conducted on site and region level according to the sample groups specified in the analysis.

Comparisons

The following comparisons were made:

P-values

In the following anlyses, p-values on the site level were computed using the limma method. I.e. hierarchical linear models from the limma package were employed and fitted using an empirical Bayes approach on derived M-values.

Site Level

Differential methylation on the site level was computed based on a variety of metrics. Of particular interest for the following plots and analyses are the following quantities for each site: a) the difference in mean methylation levels of the two groups being compared, b) the quotient in mean methylation and c) a statistical test (t-test or limma depending on the settings) assessing whether the methylation values in the two groups originate from distinct distributions. Additionally each site was assigned a rank based on each of these three criteria. A combined rank is computed as the maximum (i.e. worst) rank among the three ranks. The smaller the combined rank for a site, the more evidence for differential methylation it exhibits. This section includes scatterplots of the site group means as well as volcano plots of each pairwise comparison colored according to the combined ranks or p-values of a given site.

The following rank cutfoffs have been automatically selected for the analysis of differentially methylated sites:

Rank Cutoff
ectoderm vs. non.ectoderm (based on lineage) 35094
ectoderm, mesoderm vs. non.ectoderm, mesoderm (based on lineage) 47551
endoderm vs. non.endoderm (based on lineage) 28524
epithelial vs. non.epithelial (based on lineage) 155229
extraembryonic mesoderm, trophectoderm vs. non.extraembryonic mesoderm, trophectoderm (based on lineage) 75671
inner cell mass vs. non.inner cell mass (based on lineage) 79546
mesoderm vs. non.mesoderm (based on lineage) 47347
cancer vs. normal (based on karyotype) 136749
B vs. non.B (based on sex) 58957
F vs. non.F (based on sex) 18041
M vs. non.M (based on sex) 30798
comparison
differential methylation measure

Figure 1

Figure 1

Scatterplot for differential methylation (sites). If the selected criterion is not rankGradient: The transparency corresponds to point density. If the number of points exceeds 2e+06 then the number of points for density estimation is reduced to that number by random sampling.The1% of the points in the sparsest populated plot regions are drawn explicitly (up to a maximum of 10000 points).Additionally, the colored points represent differentially methylated sites (according to the selected criterion). If the selected criterion is rankGradient: median combined ranks accross hexagonal bins are shown as a gradient according to the color legend.

comparison
difference metric
significance metric

Figure 2

Figure 2

Volcano plot for differential methylation quantified by various metrics. Color scale according to combined ranking.

Differential Methylation Tables

A tabular overview of measures for differential methylation on the site level for the individual comparisons are provided in this section. Below, a brief explanation of the different columns can be found:

The tables for the individual comparisons can be found here:

Region Level

Differential methylation on the region level was computed based on a variety of metrics. Of particular interest for the following plots and analyses are the following quantities for each region: the mean difference in means across all sites in a region of the two groups being compared and the mean of quotients in mean methylation as well as a combined p-value calculated from all site p-values in the region [1]. Additionally each region was assigned a rank based on each of these three criteria. A combined rank is computed as the maximum (i.e. worst) value among the three ranks. The smaller the combined rank for a region, the more evidence for differential methylation it exhibits. Regions were defined based on the region types specified in the analysis. This section includes scatterplots of the region group means as well as volcano plots of each pairwise comparison colored according to the combined rank of a given region.

The following rank cutfoffs have been automatically selected for the analysis of differentially methylated regions:

tiling genes promoters cpgislands
ectoderm vs. non.ectoderm (based on lineage) 2611 2306 2048 2338
ectoderm, mesoderm vs. non.ectoderm, mesoderm (based on lineage) 2727 389 340 299
endoderm vs. non.endoderm (based on lineage) 6969 891 664 972
epithelial vs. non.epithelial (based on lineage) 15569 2245 1484 785
extraembryonic mesoderm, trophectoderm vs. non.extraembryonic mesoderm, trophectoderm (based on lineage) 3240 800 600 723
inner cell mass vs. non.inner cell mass (based on lineage) 7348 1354 1667 2570
mesoderm vs. non.mesoderm (based on lineage) 4997 1935 3186 1492
cancer vs. normal (based on karyotype) 10160 5776 4309 5114
B vs. non.B (based on sex) 5272 688 487 261
F vs. non.F (based on sex) 3422 77 163 213
M vs. non.M (based on sex) 1837 41 0 139
comparison
regions
differential methylation measure

Figure 3

Figure 3

Scatterplot for differential methylation (regions). If the selected criterion is not rankGradient: The transparency corresponds to point density. The 1% of the points in the sparsest populated plot regions are drawn explicitly. Additionally, the colored points represent differentially methylated regions (according to the selected criterion). If the selected criterion is rankGradient: median combined ranks accross hexagonal bins are shown as a gradient according to the color legend.

comparison
regions
difference metric
significance metric

Figure 4

Figure 4

Volcano plot for differential methylation quantified by various metrics. Color scale according to combined ranking.

Differential Methylation Tables

A tabular overview of measures for differential methylation on the region level for the individual comparisons are provided in this section.

The tables for the individual comparisons can be found here:

tiling genes promoters cpgislands
ectoderm vs. non.ectoderm (based on lineage) csv csv csv csv
ectoderm, mesoderm vs. non.ectoderm, mesoderm (based on lineage) csv csv csv csv
endoderm vs. non.endoderm (based on lineage) csv csv csv csv
epithelial vs. non.epithelial (based on lineage) csv csv csv csv
extraembryonic mesoderm, trophectoderm vs. non.extraembryonic mesoderm, trophectoderm (based on lineage) csv csv csv csv
inner cell mass vs. non.inner cell mass (based on lineage) csv csv csv csv
mesoderm vs. non.mesoderm (based on lineage) csv csv csv csv
cancer vs. normal (based on karyotype) csv csv csv csv
B vs. non.B (based on sex) csv csv csv csv
F vs. non.F (based on sex) csv csv csv csv
M vs. non.M (based on sex) csv csv csv csv

Enrichment Analysis

Enrichment Analysis was conducted. The wordclouds and tables below contains significant GO terms as determined by a hypergeometric test.

comparison
Hypermethylation/hypomethylation
ontology
regions
differential methylation measure

Figure 5

Figure 5

Wordclouds for GO enrichment terms.

comparison
Hypermethylation/hypomethylation
ontology
regions
differential methylation measure

GOMFID Pvalue OddsRatio ExpCount Count Size Term
GO:0007205 3e-04 27.6757 0.1265 3 32 protein kinase C-activating G-protein coupled receptor signaling pathway
GO:0030001 5e-04 4.4379 2.3828 9 603 metal ion transport
GO:0034377 0.0012 47.697 0.0514 2 13 plasma lipoprotein particle assembly
GO:0034367 0.002 34.9667 0.0672 2 17 macromolecular complex remodeling
GO:0034369 0.002 34.9667 0.0672 2 17 plasma lipoprotein particle remodeling
GO:0003009 0.0034 26.2146 0.0869 2 22 skeletal muscle contraction
GO:0010625 0.004 Inf 0.004 1 1 positive regulation of Schwann cell proliferation
GO:0010730 0.004 Inf 0.004 1 1 negative regulation of hydrogen peroxide biosynthetic process
GO:0010903 0.004 Inf 0.004 1 1 negative regulation of very-low-density lipoprotein particle remodeling
GO:0042930 0.004 Inf 0.004 1 1 enterobactin transport
GO:0060345 0.004 Inf 0.004 1 1 spleen trabecula formation
GO:0060354 0.004 Inf 0.004 1 1 negative regulation of cell adhesion molecule production
GO:0071502 0.004 Inf 0.004 1 1 cellular response to temperature stimulus
GO:2000057 0.004 Inf 0.004 1 1 negative regulation of Wnt signaling pathway involved in digestive tract morphogenesis
GO:0006820 0.0041 4.3626 1.5332 6 388 anion transport
GO:0007218 0.0047 9.6283 0.3398 3 86 neuropeptide signaling pathway
GO:0031102 0.005 20.9633 0.1067 2 27 neuron projection regeneration
GO:0071825 0.005 20.9633 0.1067 2 27 protein-lipid complex subunit organization
GO:0048878 0.0052 3.3346 2.7227 8 689 chemical homeostasis
GO:0055085 0.0058 2.8726 4.0267 10 1019 transmembrane transport
GO:0034381 0.0058 19.4074 0.1146 2 29 plasma lipoprotein particle clearance
GO:0071312 0.0058 19.4074 0.1146 2 29 cellular response to alkaloid
GO:0051051 0.0065 4.6197 1.1894 5 301 negative regulation of transport
GO:0033344 0.007 17.4625 0.1265 2 32 cholesterol efflux
GO:0050879 0.0075 16.8978 0.1304 2 33 multicellular organismal movement
GO:0016125 0.0078 7.9806 0.407 3 103 sterol metabolic process
GO:0002740 0.0079 257.1837 0.0079 1 2 negative regulation of cytokine secretion involved in immune response
GO:0007198 0.0079 257.1837 0.0079 1 2 adenylate cyclase-inhibiting serotonin receptor signaling pathway
GO:0018916 0.0079 257.1837 0.0079 1 2 nitrobenzene metabolic process
GO:0034395 0.0079 257.1837 0.0079 1 2 regulation of transcription from RNA polymerase II promoter in response to iron
GO:0050713 0.0079 257.1837 0.0079 1 2 negative regulation of interleukin-1 beta secretion
GO:0050968 0.0079 257.1837 0.0079 1 2 detection of chemical stimulus involved in sensory perception of pain
GO:0060741 0.0079 257.1837 0.0079 1 2 prostate gland stromal morphogenesis
GO:0070458 0.0079 257.1837 0.0079 1 2 cellular detoxification of nitrogen compound
GO:1903426 0.0079 257.1837 0.0079 1 2 regulation of reactive oxygen species biosynthetic process
GO:2000382 0.0079 257.1837 0.0079 1 2 positive regulation of mesoderm development
GO:0006695 0.0079 16.3685 0.1344 2 34 cholesterol biosynthetic process
GO:0055081 0.0079 16.3685 0.1344 2 34 anion homeostasis
GO:0046165 0.0093 7.4544 0.4347 3 110 alcohol biosynthetic process
GO:0006694 0.0095 7.3848 0.4386 3 111 steroid biosynthetic process

References

  1. Makambi, K. (2003) Weighted inverse chi-square method for correlated significance tests. Journal of Applied Statistics, 30(2), 225234