Quality Control

Quality Control

This section contains quality control plots and statistics for the methylation data.

Quality Control Box Plots

Each box plot below shows the signal distribution of quality control probes across all samples. The control box plots are separated by control types. Detailed description of the control probes is given in the RnBeads vignette.

Control probe type

Figure 1

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Quality control box plots.

Quality Control Bar Plots

The plots below visualize the exact signal levels at each quality control probe. Note that the scale is not standardized. Background signal is usualy at the level of 1000 to 2000.

Samples #:
Control probe ID

Figure 2

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Quality control bar plots.

Negative Control Box Plots

Negative control box plots visualize background intensity distributions of all analyzed samples. Samples with skewed distributions and high medians are likely to be of low quality and should be discarded from the analysis.

Samples #:

Figure 3

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Box plots of the negative control probes.

Visualization of SNP Probe Data

Analysis of the values of the SNP-based probes can help identify sample mixups.

SNP Heatmap

SNP heatmap enables the identification of sample mixups in particular for genetically matched designs.

Figure 4

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Heatmap of the SNP probes. Euclidean distance and complete linkage are used for constructing the dendrograms. Samples with the same genetic background are expected to cluster together.

SNP-based Distances

If we inspect the dataset in the space defined by the SNP probes only, samples appearing close to each other are genetically similar.

The figure below shows the relative distances between all pairs of samples based on the β values of the considered SNP probes. The distance metric used is average absolute difference, which can be considered a scaled version of Manhattan distance.

Figure 5

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Distances between pairs of samples based on 65 SNP probes.

The full table of all pairwise distances is stored in a dedicated comma-separated file accompanying this report.

Gender Prediction

RnBeads predicted the gender of the samples in the dataset using a logistic regression model. The results are summarized in the table below.

Gender Samples
1 female 6
2 male 6
3 unknown 0

Gender was predicted based on the increase (or decrease) of mean signal intensities in the sex chromosomes w.r.t. the corresponding value in autosomes. The figure below displays these characteristics of the samples.

Colors denote

Figure 6

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Gender prediction based on mean signal increase. The decision boundary between the two genders is visualized by a black line. Sample colors denote predicted male probability / gender.