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 (limma or t-test 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
blood vs. skin (based on tissue) 136763
lymphoid vs. multi (based on blood_lineage) 492830
lymphoid vs. myeloid (based on blood_lineage) 519017
multi vs. myeloid (based on blood_lineage) 528486
differentiated vs. progenitor (based on differentiation_level_blood) 457021
differentiated vs. stemCell (based on differentiation_level_blood) 594371
progenitor vs. stemCell (based on differentiation_level_blood) 540603
differentiated vs. progenitor (based on differentiation_level_skin) 4838
differentiated vs. stemCell (based on differentiation_level_skin) 549082
progenitor vs. stemCell (based on differentiation_level_skin) 507161
CLP vs. CMP (based on cmp_blood_CLP_CMP) 616010
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
blood vs. skin (based on tissue) 11848 2604 3178 722
lymphoid vs. multi (based on blood_lineage) 20549 924 1326 576
lymphoid vs. myeloid (based on blood_lineage) 3824 269 259 142
multi vs. myeloid (based on blood_lineage) 24432 1929 3492 1402
differentiated vs. progenitor (based on differentiation_level_blood) 1103 165 231 148
differentiated vs. stemCell (based on differentiation_level_blood) 34831 6192 5886 2720
progenitor vs. stemCell (based on differentiation_level_blood) 32326 3577 4475 1796
differentiated vs. progenitor (based on differentiation_level_skin) 17090 1585 1850 1200
differentiated vs. stemCell (based on differentiation_level_skin) 12389 1056 1228 668
progenitor vs. stemCell (based on differentiation_level_skin) 11766 1112 1225 687
CLP vs. CMP (based on cmp_blood_CLP_CMP) 22567 2511 2787 1771
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
blood vs. skin (based on tissue) csv csv csv csv
lymphoid vs. multi (based on blood_lineage) csv csv csv csv
lymphoid vs. myeloid (based on blood_lineage) csv csv csv csv
multi vs. myeloid (based on blood_lineage) csv csv csv csv
differentiated vs. progenitor (based on differentiation_level_blood) csv csv csv csv
differentiated vs. stemCell (based on differentiation_level_blood) csv csv csv csv
progenitor vs. stemCell (based on differentiation_level_blood) csv csv csv csv
differentiated vs. progenitor (based on differentiation_level_skin) csv csv csv csv
differentiated vs. stemCell (based on differentiation_level_skin) csv csv csv csv
progenitor vs. stemCell (based on differentiation_level_skin) csv csv csv csv
CLP vs. CMP (based on cmp_blood_CLP_CMP) csv csv csv csv

GO Enrichment Analysis

GO 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:0032946 6e-04 11.6298 0.3818 4 117 positive regulation of mononuclear cell proliferation
GO:0051251 6e-04 8.096 0.6885 5 211 positive regulation of lymphocyte activation
GO:0022407 9e-04 5.8745 1.1454 6 351 regulation of cell-cell adhesion
GO:0050867 0.0016 6.4939 0.8517 5 261 positive regulation of cell activation
GO:0002376 0.0016 2.8717 5.9391 14 1820 immune system process
GO:0033599 0.0017 37.3318 0.062 2 19 regulation of mammary gland epithelial cell proliferation
GO:1903039 0.0018 8.4559 0.5189 4 159 positive regulation of leukocyte cell-cell adhesion
GO:0042110 0.002 5.023 1.3314 6 408 T cell activation
GO:0060749 0.0021 33.3979 0.0685 2 21 mammary gland alveolus development
GO:1903708 0.0021 8.0368 0.545 4 167 positive regulation of hemopoiesis
GO:0002694 0.0022 4.9348 1.3543 6 415 regulation of leukocyte activation
GO:0042102 0.0023 12.5677 0.2611 3 80 positive regulation of T cell proliferation
GO:0060216 0.0025 30.2133 0.0751 2 23 definitive hemopoiesis
GO:0006958 0.003 27.5826 0.0816 2 25 complement activation, classical pathway
GO:0030878 0.0032 26.4317 0.0848 2 26 thyroid gland development
GO:0035702 0.0033 Inf 0.0033 1 1 monocyte homeostasis
GO:0097052 0.0033 Inf 0.0033 1 1 L-kynurenine metabolic process
GO:1905221 0.0033 Inf 0.0033 1 1 positive regulation of platelet formation
GO:1990959 0.0033 Inf 0.0033 1 1 eosinophil homeostasis
GO:1990960 0.0033 Inf 0.0033 1 1 basophil homeostasis
GO:0050670 0.0035 6.9947 0.6233 4 191 regulation of lymphocyte proliferation
GO:0070663 0.0041 6.6696 0.6527 4 200 regulation of leukocyte proliferation
GO:0002460 0.0046 6.4368 0.6755 4 207 adaptive immune response based on somatic recombination of immune receptors built from immunoglobulin superfamily domains
GO:0043588 0.0059 5.9881 0.7244 4 222 skin development
GO:0001817 0.0064 3.9397 1.6806 6 515 regulation of cytokine production
GO:0001869 0.0065 311.4118 0.0065 1 2 negative regulation of complement activation, lectin pathway
GO:0060574 0.0065 311.4118 0.0065 1 2 intestinal epithelial cell maturation
GO:0060764 0.0065 311.4118 0.0065 1 2 cell-cell signaling involved in mammary gland development
GO:0090271 0.0065 311.4118 0.0065 1 2 positive regulation of fibroblast growth factor production
GO:0097535 0.0065 311.4118 0.0065 1 2 lymphoid lineage cell migration into thymus
GO:0097536 0.0065 311.4118 0.0065 1 2 thymus epithelium morphogenesis
GO:1902232 0.0065 311.4118 0.0065 1 2 regulation of positive thymic T cell selection
GO:1903860 0.0065 311.4118 0.0065 1 2 negative regulation of dendrite extension
GO:2000813 0.0065 311.4118 0.0065 1 2 negative regulation of barbed-end actin filament capping
GO:0045580 0.0066 8.4689 0.3818 3 117 regulation of T cell differentiation
GO:0051142 0.0098 155.6961 0.0098 1 3 positive regulation of NK T cell proliferation
GO:0060435 0.0098 155.6961 0.0098 1 3 bronchiole development

LOLA Enrichment Analysis

No LOLA Enrichment Analysis was conducted

References

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