Preprocessing

The table below lists the options of the executed module.

4713 sites were removed because they overlap with SNPs. The list of removed probes is available in a dedicated table accompanying this report.

The Greedycut algorithm iteratively removes from the dataset probes and samples of highest impurity. These correspond to the rows and columns in the detection p-value table that contain the largest fraction of unreliable measurements. This section summarizes the results of applying Greedycut on the analyzed dataset.

Unreliable Measurements

We considered every β value to be unreliable when its corresponding detection p-value is not below the threshold T:

p ≥ T = 0.05

The figure below summarizes the observed number of unreliable measurements per probe and per sample.

Number of values per

probe sample

Figure 1

Cumulative distribution function of number of unreliable values per probe/sample.

Filtered Probes and Samples

RnBeads executed Greedycut using the threshold given above and applied all its steps. Briefly, Greedycut is an iterative algorithm that filters out the probe or sample with the highest fraction of unreliable measurements one at a time. Note that every iteration of the algorithm produces a matrix of retained measurements and a set of removed ones.

We calculated false positive rate (α) and sensitivity (s) when the retained measurements are considered as prediction for the reliable ones. Among all matrices produced by Greedycut, we selected the one that maximizes the value of the expression s + 1 - α, thereby giving equal weights to the sensitivity and specificity. Presented geometrically on a ROC curve, this is the point that is furthest from the diagonal. The results of the Greedycut procedure and the selected iteration are presented in the figure below.

Metric	table dimensions false positive rate sensitivity ROC curve distance to the diagonal in a ROC plot
Iterations to show	all executed only

Figure 2

Change of table dimensions / metric related to accuracy as Greedycut progressively removes probes and samples. Accuracy is calculated by treating the retained entries as predictive of reliable measurements. The red circle, if present, marks the last iteration that was executed.

Based on the criteria described above, 16762 probes and 26 samples were filtered out. Links to the lists of removed items are given below.

Type	Removed	Table
Probes	16762	removed_sites_greedycut.csv
Samples	26	removed_samples_greedycut.csv

As a final outcome of the filtering procedures, 21475 probes and 26 samples were removed. These statistics are presented in a dedicated table that accompanies this report and visualized in the figure below.

Figure 3

Fractions of removed values in the dataset after applying filtering procedures.

The figure below compares the distributions of the removed methylation β values and of the retained ones.

Plot type

density estimation histograms quantile-quantile plot

Figure 4

Comparison of removed and retained β values.Both distributions are estimated by randomly sampling 1000000 values in each group.

The measurements in this dataset were not normalized after loading.

Sample Mean Methylations

The following figure visualizes the average methylation per sample. Samples are grouped by slide.

Slide number

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Figure 5

Point-and-whisker plot showing mean and standard deviation among all beta values in a sample.

Region Annotations

The studied dataset contains in total 2414 probes of the specified contexts. All these (removed) probes are available in a dedicated table accompanying this report. The table below summarizes the number of removed probes per context.

10555 probes on sex chromosomes were removed at this step. The list of removed probes is available in a dedicated table accompanying this report.

As a final outcome of the filtering procedures, 12969 probes and 0 samples were removed. These statistics are presented in a dedicated table that accompanies this report and visualized in the figure below.

Figure 6

Fractions of removed values in the dataset after applying filtering procedures.

The figure below compares the distributions of the removed methylation β values and of the retained ones.

Plot type

density estimation histograms quantile-quantile plot

Figure 7

Comparison of removed and retained β values.Both distributions are estimated by randomly sampling 1000000 values in each group.