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
BrM_ERP vs. BrM_HER2P (based on Tiss_Subprim) 45
BrM_ERP vs. BrM_TNBC (based on Tiss_Subprim) 73153
BrM_ERP vs. Bx_ERP (based on Tiss_Subprim) 0
BrM_ERP vs. Bx_HER2P (based on Tiss_Subprim) 201
BrM_ERP vs. Bx_TNBC (based on Tiss_Subprim) 76661
BrM_HER2P vs. BrM_TNBC (based on Tiss_Subprim) 81041
BrM_HER2P vs. Bx_ERP (based on Tiss_Subprim) 95461
BrM_HER2P vs. Bx_HER2P (based on Tiss_Subprim) 87803
BrM_HER2P vs. Bx_TNBC (based on Tiss_Subprim) 79388
BrM_TNBC vs. Bx_ERP (based on Tiss_Subprim) 71052
BrM_TNBC vs. Bx_HER2P (based on Tiss_Subprim) 75153
BrM_TNBC vs. Bx_TNBC (based on Tiss_Subprim) 56404
Bx_ERP vs. Bx_HER2P (based on Tiss_Subprim) 4
Bx_ERP vs. Bx_TNBC (based on Tiss_Subprim) 67795
Bx_HER2P vs. Bx_TNBC (based on Tiss_Subprim) 61717
NT vs. YT (based on NT) 97803
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
BrM_ERP vs. BrM_HER2P (based on Tiss_Subprim) 0 10 40 0
BrM_ERP vs. BrM_TNBC (based on Tiss_Subprim) 6873 19 305 355
BrM_ERP vs. Bx_ERP (based on Tiss_Subprim) 46 11 0 12
BrM_ERP vs. Bx_HER2P (based on Tiss_Subprim) 6 0 0 1
BrM_ERP vs. Bx_TNBC (based on Tiss_Subprim) 77 0 60 177
BrM_HER2P vs. BrM_TNBC (based on Tiss_Subprim) 10318 1021 1185 1329
BrM_HER2P vs. Bx_ERP (based on Tiss_Subprim) 1958 45 13 0
BrM_HER2P vs. Bx_HER2P (based on Tiss_Subprim) 155 0 0 0
BrM_HER2P vs. Bx_TNBC (based on Tiss_Subprim) 5120 343 2972 1537
BrM_TNBC vs. Bx_ERP (based on Tiss_Subprim) 8917 220 1549 1316
BrM_TNBC vs. Bx_HER2P (based on Tiss_Subprim) 5505 1475 1249 2321
BrM_TNBC vs. Bx_TNBC (based on Tiss_Subprim) 94 0 71 39
Bx_ERP vs. Bx_HER2P (based on Tiss_Subprim) 93 0 25 2
Bx_ERP vs. Bx_TNBC (based on Tiss_Subprim) 4104 9 3 70
Bx_HER2P vs. Bx_TNBC (based on Tiss_Subprim) 3087 46 1351 872
NT vs. YT (based on NT) 6882 1380 2098 2799
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
BrM_ERP vs. BrM_HER2P (based on Tiss_Subprim) csv csv csv csv
BrM_ERP vs. BrM_TNBC (based on Tiss_Subprim) csv csv csv csv
BrM_ERP vs. Bx_ERP (based on Tiss_Subprim) csv csv csv csv
BrM_ERP vs. Bx_HER2P (based on Tiss_Subprim) csv csv csv csv
BrM_ERP vs. Bx_TNBC (based on Tiss_Subprim) csv csv csv csv
BrM_HER2P vs. BrM_TNBC (based on Tiss_Subprim) csv csv csv csv
BrM_HER2P vs. Bx_ERP (based on Tiss_Subprim) csv csv csv csv
BrM_HER2P vs. Bx_HER2P (based on Tiss_Subprim) csv csv csv csv
BrM_HER2P vs. Bx_TNBC (based on Tiss_Subprim) csv csv csv csv
BrM_TNBC vs. Bx_ERP (based on Tiss_Subprim) csv csv csv csv
BrM_TNBC vs. Bx_HER2P (based on Tiss_Subprim) csv csv csv csv
BrM_TNBC vs. Bx_TNBC (based on Tiss_Subprim) csv csv csv csv
Bx_ERP vs. Bx_HER2P (based on Tiss_Subprim) csv csv csv csv
Bx_ERP vs. Bx_TNBC (based on Tiss_Subprim) csv csv csv csv
Bx_HER2P vs. Bx_TNBC (based on Tiss_Subprim) csv csv csv csv
NT vs. YT (based on NT) csv csv csv csv

GO Enrichment Analysis

GO Enrichment Analysis was conducted using a hypergeometric test that addresses the hierarchical structure of the ontology (see [2] for details). The wordclouds and tables below contain significant GO terms according to these tests.

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:0006335 0 262.3377 0.075 10 32 DNA replication-dependent chromatin assembly
GO:0006334 0 70.4815 0.2436 11 104 nucleosome assembly
GO:0040029 0 46.6289 0.3116 10 133 regulation of gene expression, epigenetic
GO:0071824 0 32.7216 0.492 11 210 protein-DNA complex subunit organization
GO:0032200 0 39.227 0.3655 10 156 telomere organization
GO:0006338 0 28.7637 0.5552 11 237 chromatin remodeling
GO:0009593 0 15.2 0.6724 8 287 detection of chemical stimulus
GO:0007606 0 14.6648 0.6958 8 297 sensory perception of chemical stimulus
GO:0050906 0 13.8815 0.7333 8 313 detection of stimulus involved in sensory perception
GO:0050911 0 17.3415 0.5037 7 215 detection of chemical stimulus involved in sensory perception of smell
GO:0065003 0 5.5207 3.294 13 1406 protein-containing complex assembly
GO:0007186 1e-04 5.638 2.2819 10 974 G protein-coupled receptor signaling pathway
GO:0035195 1e-04 9.9941 0.7122 6 304 miRNA-mediated gene silencing
GO:0016441 1e-04 9.6 0.7403 6 316 post-transcriptional gene silencing
GO:0031047 1e-04 8.9514 0.7919 6 338 gene silencing by RNA
GO:0050877 4e-04 4.4231 2.8559 10 1219 nervous system process
GO:0050789 7e-04 4.508 24.8523 34 10608 regulation of biological process
GO:0010467 0.0038 2.5135 13.457 22 5744 gene expression
GO:0002032 0.0047 437.3243 0.0047 1 2 desensitization of G protein-coupled receptor signaling pathway by arrestin
GO:0061885 0.0047 437.3243 0.0047 1 2 positive regulation of mini excitatory postsynaptic potential
GO:0002025 0.007 218.6486 0.007 1 3 norepinephrine-epinephrine-mediated vasodilation involved in regulation of systemic arterial blood pressure
GO:0044245 0.007 218.6486 0.007 1 3 polysaccharide digestion
GO:0099601 0.0084 15.7164 0.1382 2 59 regulation of neurotransmitter receptor activity
GO:0014054 0.0093 145.7568 0.0094 1 4 positive regulation of gamma-aminobutyric acid secretion
GO:0044278 0.0093 145.7568 0.0094 1 4 cell wall disruption in another organism
GO:0051919 0.0093 145.7568 0.0094 1 4 positive regulation of fibrinolysis
GO:1990911 0.0093 145.7568 0.0094 1 4 response to psychosocial stress

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
  2. Falcon, S., & Gentleman, R. (2007). Using GOstats to test gene lists for GO term association. Bioinformatics, 23(2), 257-258