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:

The table below summarizes information on the comparisons.

comparison adjustment covariateTable
1 CMP vs. MEP (based on cmp_ct_CMPvMEP) flowcell csv
2 CMP vs. GMP (based on cmp_ct_CMPvGMP) flowcell csv
3 CLP vs. CMP (based on cmp_ct_CMPvCLP) sex,flowcell csv
4 GMP vs. MLP3 (based on cmp_ct_MLP3vGMP) flowcell csv
5 CLP vs. MLP0 (based on cmp_ct_CLPvMLP0) flowcell csv
6 CLP vs. MLP1 (based on cmp_ct_CLPvMLP1) sex csv
7 CLP vs. MLP2 (based on cmp_ct_CLPvMLP2) sex,flowcell csv
8 CLP vs. MLP3 (based on cmp_ct_CLPvMLP3) sex,flowcell csv
9 MLP1 vs. MLP2 (based on cmp_ct_MLP1vMLP2) sex,flowcell csv
10 MLP2 vs. MLP3 (based on cmp_ct_MLP2vMLP3) sex,flowcell csv
11 MLP1 vs. MLP3 (based on cmp_ct_MLP1vMLP3) sex,flowcell csv
12 MLP0 vs. MLP1 (based on cmp_ct_MLP0vMLP1) flowcell csv
13 MLP0 vs. MLP2 (based on cmp_ct_MLP0vMLP2) flowcell csv
14 MLP0 vs. MLP3 (based on cmp_ct_MLP0vMLP3) flowcell csv
15 HSC vs. MPP (based on cmp_ct_HSCvMPP) donorId,flowcell,cellSourceCurated csv
16 CMP vs. MPP (based on cmp_ct_MPPvCMP) flowcell,cellSourceCurated csv
17 HSC vs. ML (based on cmp_ct_HSCvML) donorId,flowcell,cellSourceCurated csv
18 LYM vs. MYE (based on cmp_ct_MYEvLYM) flowcell csv
19 BM vs. CB (based on cmp_src_HSC_BMvCB) flowcell csv
20 BM vs. FL (based on cmp_src_HSC_BMvFL) donorId,flowcell csv
21 BM vs. PB (based on cmp_src_HSC_BMvPB) flowcell csv
22 CB vs. FL (based on cmp_src_HSC_CBvFL) flowcell csv
23 CB vs. PB (based on cmp_src_HSC_CBvPB) csv
24 FL vs. PB (based on cmp_src_HSC_FLvPB) flowcell csv
25 BM vs. CB (based on cmp_src_MPP_BMvCB) csv
26 BM vs. PB (based on cmp_src_MPP_BMvPB) flowcell csv
27 CB vs. PB (based on cmp_src_MPP_CBvPB) flowcell csv
28 HSC vs. MPP (based on cmp_HSCvMPP_PB) flowcell csv
29 HSC vs. MPP (based on cmp_HSCvMPP_CB) csv
30 HSC vs. MPP (based on cmp_HSCvMPP_BM) flowcell csv

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.

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 methylation difference in a region of the two groups being and of quotient of mean methylation levelsas well as a p-value obtained from statistical testing (limma or t-test; depending on parameter settings). 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 cpgislands genes promoters ensembleRegBuildBPall ensembleRegBuildBPallMerged
CMP vs. MEP (based on cmp_ct_CMPvMEP) 0 0 0 0 0 0
CMP vs. GMP (based on cmp_ct_CMPvGMP) 0 0 0 0 0 0
CLP vs. CMP (based on cmp_ct_CMPvCLP) 0 0 0 0 0 0
GMP vs. MLP3 (based on cmp_ct_MLP3vGMP) 0 0 0 0 0 0
CLP vs. MLP0 (based on cmp_ct_CLPvMLP0) 0 0 0 0 0 0
CLP vs. MLP1 (based on cmp_ct_CLPvMLP1) 0 0 0 0 0 0
CLP vs. MLP2 (based on cmp_ct_CLPvMLP2) 0 0 0 0 0 0
CLP vs. MLP3 (based on cmp_ct_CLPvMLP3) 0 0 0 0 0 0
MLP1 vs. MLP2 (based on cmp_ct_MLP1vMLP2) 0 0 0 0 0 0
MLP2 vs. MLP3 (based on cmp_ct_MLP2vMLP3) 0 0 0 0 0 0
MLP1 vs. MLP3 (based on cmp_ct_MLP1vMLP3) 0 0 0 0 0 0
MLP0 vs. MLP1 (based on cmp_ct_MLP0vMLP1) 0 0 0 0 0 0
MLP0 vs. MLP2 (based on cmp_ct_MLP0vMLP2) 0 0 0 0 0 0
MLP0 vs. MLP3 (based on cmp_ct_MLP0vMLP3) 0 0 0 0 0 0
HSC vs. MPP (based on cmp_ct_HSCvMPP) 0 0 0 0 0 0
CMP vs. MPP (based on cmp_ct_MPPvCMP) 0 0 0 0 0 0
HSC vs. ML (based on cmp_ct_HSCvML) 0 0 0 0 0 0
LYM vs. MYE (based on cmp_ct_MYEvLYM) 0 0 0 0 0 0
BM vs. CB (based on cmp_src_HSC_BMvCB) 0 0 0 0 0 0
BM vs. FL (based on cmp_src_HSC_BMvFL) 0 0 0 0 0 0
BM vs. PB (based on cmp_src_HSC_BMvPB) 0 0 0 0 0 0
CB vs. FL (based on cmp_src_HSC_CBvFL) 0 0 0 0 0 0
CB vs. PB (based on cmp_src_HSC_CBvPB) 0 0 0 0 0 0
FL vs. PB (based on cmp_src_HSC_FLvPB) 0 0 0 0 0 0
BM vs. CB (based on cmp_src_MPP_BMvCB) 0 0 0 0 0 0
BM vs. PB (based on cmp_src_MPP_BMvPB) 0 0 0 0 0 0
CB vs. PB (based on cmp_src_MPP_CBvPB) 0 0 0 0 0 0
HSC vs. MPP (based on cmp_HSCvMPP_PB) 0 0 0 0 0 0
HSC vs. MPP (based on cmp_HSCvMPP_CB) 0 0 0 0 0 0
HSC vs. MPP (based on cmp_HSCvMPP_BM) 0 0 0 0 0 0
comparison
regions
differential methylation measure

Figure 1

Figure 1

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 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 region level for the individual comparisons are provided in this section.

The tables for the individual comparisons can be found here:

tiling cpgislands genes promoters ensembleRegBuildBPall ensembleRegBuildBPallMerged
CMP vs. MEP (based on cmp_ct_CMPvMEP) csv csv csv csv csv csv
CMP vs. GMP (based on cmp_ct_CMPvGMP) csv csv csv csv csv csv
CLP vs. CMP (based on cmp_ct_CMPvCLP) csv csv csv csv csv csv
GMP vs. MLP3 (based on cmp_ct_MLP3vGMP) csv csv csv csv csv csv
CLP vs. MLP0 (based on cmp_ct_CLPvMLP0) csv csv csv csv csv csv
CLP vs. MLP1 (based on cmp_ct_CLPvMLP1) csv csv csv csv csv csv
CLP vs. MLP2 (based on cmp_ct_CLPvMLP2) csv csv csv csv csv csv
CLP vs. MLP3 (based on cmp_ct_CLPvMLP3) csv csv csv csv csv csv
MLP1 vs. MLP2 (based on cmp_ct_MLP1vMLP2) csv csv csv csv csv csv
MLP2 vs. MLP3 (based on cmp_ct_MLP2vMLP3) csv csv csv csv csv csv
MLP1 vs. MLP3 (based on cmp_ct_MLP1vMLP3) csv csv csv csv csv csv
MLP0 vs. MLP1 (based on cmp_ct_MLP0vMLP1) csv csv csv csv csv csv
MLP0 vs. MLP2 (based on cmp_ct_MLP0vMLP2) csv csv csv csv csv csv
MLP0 vs. MLP3 (based on cmp_ct_MLP0vMLP3) csv csv csv csv csv csv
HSC vs. MPP (based on cmp_ct_HSCvMPP) csv csv csv csv csv csv
CMP vs. MPP (based on cmp_ct_MPPvCMP) csv csv csv csv csv csv
HSC vs. ML (based on cmp_ct_HSCvML) csv csv csv csv csv csv
LYM vs. MYE (based on cmp_ct_MYEvLYM) csv csv csv csv csv csv
BM vs. CB (based on cmp_src_HSC_BMvCB) csv csv csv csv csv csv
BM vs. FL (based on cmp_src_HSC_BMvFL) csv csv csv csv csv csv
BM vs. PB (based on cmp_src_HSC_BMvPB) csv csv csv csv csv csv
CB vs. FL (based on cmp_src_HSC_CBvFL) csv csv csv csv csv csv
CB vs. PB (based on cmp_src_HSC_CBvPB) csv csv csv csv csv csv
FL vs. PB (based on cmp_src_HSC_FLvPB) csv csv csv csv csv csv
BM vs. CB (based on cmp_src_MPP_BMvCB) csv csv csv csv csv csv
BM vs. PB (based on cmp_src_MPP_BMvPB) csv csv csv csv csv csv
CB vs. PB (based on cmp_src_MPP_CBvPB) csv csv csv csv csv csv
HSC vs. MPP (based on cmp_HSCvMPP_PB) csv csv csv csv csv csv
HSC vs. MPP (based on cmp_HSCvMPP_CB) csv csv csv csv csv csv
HSC vs. MPP (based on cmp_HSCvMPP_BM) csv csv 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 3

Figure 3

Wordclouds for GO enrichment terms.

comparison
Hypermethylation/hypomethylation
ontology
regions
differential methylation measure

GOMFID Pvalue OddsRatio ExpCount Count Size Term
GO:0060764 1e-04 Inf 1e-04 1 2 cell-cell signaling involved in mammary gland development
GO:0060435 2e-04 Inf 2e-04 1 3 bronchiole development
GO:0060480 3e-04 Inf 3e-04 1 4 lung goblet cell differentiation
GO:0060535 3e-04 Inf 3e-04 1 4 trachea cartilage morphogenesis
GO:0060574 3e-04 Inf 3e-04 1 4 intestinal epithelial cell maturation
GO:0060482 4e-04 Inf 4e-04 1 6 lobar bronchus development
GO:0045647 4e-04 Inf 4e-04 1 7 negative regulation of erythrocyte differentiation
GO:0060638 6e-04 Inf 6e-04 1 9 mesenchymal-epithelial cell signaling
GO:0010870 7e-04 Inf 7e-04 1 11 positive regulation of receptor biosynthetic process
GO:0060484 7e-04 Inf 7e-04 1 11 lung-associated mesenchyme development
GO:0060644 0.001 Inf 0.001 1 15 mammary gland epithelial cell differentiation
GO:0002070 0.001 Inf 0.001 1 16 epithelial cell maturation
GO:0033599 0.001 Inf 0.001 1 16 regulation of mammary gland epithelial cell proliferation
GO:0060575 0.0011 Inf 0.0011 1 17 intestinal epithelial cell differentiation
GO:0060749 0.0011 Inf 0.0011 1 17 mammary gland alveolus development
GO:0060438 0.0012 Inf 0.0012 1 19 trachea development
GO:0030878 0.0017 Inf 0.0017 1 26 thyroid gland development
GO:0003016 0.0017 Inf 0.0017 1 27 respiratory system process
GO:0060487 0.0018 Inf 0.0018 1 29 lung epithelial cell differentiation
GO:0060441 0.002 Inf 0.002 1 31 epithelial tube branching involved in lung morphogenesis
GO:0048286 0.003 Inf 0.003 1 47 lung alveolus development
GO:0002066 0.0036 Inf 0.0036 1 57 columnar/cuboidal epithelial cell development
GO:0016525 0.0044 Inf 0.0044 1 69 negative regulation of angiogenesis
GO:1901343 0.0048 Inf 0.0048 1 76 negative regulation of vasculature development
GO:0045639 0.005 Inf 0.005 1 78 positive regulation of myeloid cell differentiation
GO:0048704 0.006 Inf 0.006 1 95 embryonic skeletal system morphogenesis
GO:0034101 0.0064 Inf 0.0064 1 100 erythrocyte homeostasis
GO:1903707 0.0083 Inf 0.0083 1 130 negative regulation of hemopoiesis
GO:0043112 0.0092 Inf 0.0092 1 145 receptor metabolic process
GO:0035264 0.0097 Inf 0.0097 1 153 multicellular organism growth
GO:0055123 0.0099 Inf 0.0099 1 155 digestive system development

References

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