Analyzing differences in copy number of DNA regions using qbase+

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In copy number analysis you test for DNA copy number variation in patient's samples, e.g. tumor samples. Until recently, it was thought that genes were almost always present in two copies in a genome. However, recent studies have revealed that large segments of DNA, ranging in size from thousands to millions of DNA bases, can vary in copy-number. These studies revealed that copy number variations comprise at least three times the total nucleotide content of SNPs. Such copy number variations can lead to dosage imbalances of gene products, which in its turn can lead to diseases or differences in drug response.

So in contrast to gene expression analysis where you start from RNA samples, for copy number analysis you start from genomic DNA samples.

The experiment consists of a single run: Run11
The following samples were used:

  • 2 samples of interest
  • 1 positive control: a calibrator sample containing 1 allele of the targets called SNJB-6
  • 1 positive control: a calibrator sample containing 2 alleles of the targets called gDNA
  • 1 no template control: NTC to detect the presence of contaminating DNA

The copy number of the following DNA regions was measured:

  • 2 reference genes: ZNF80 and GPR15
  • 3 regions of interest: 3 exons of VHL
There are two technical replicates per reaction.

Creating a new experiment

Loading the data

Analyzing the data

For copy number analysis you can also use the multiple reference targets normalization strategy. Just like in gene expression analysis, there is technical variability between the different samples e.g.

  • differences in the amount of gDNA used as a template
  • pipetting variation
  • ...
To remove this variability as much as possible you can use reference targets just like in gene expression analysis. In copy number analysis reference targets are genes for which you are certain that they have the same copy number in all samples that you study.

Now close the analysis wizard by clicking the Close wizard button (red) in the top menu.


For copy number analysis you need at least two positive controls with different copy numbers as is the case in our data. These positive control samples are used as a reference points to determine the true copy number in the samples of interest. The NRQs of the positive controls are set to 1 and 2 respectively and the NRQs of the samples of interest are scaled accordingly.
Thresholds are defined to determine how much the scaled NRQs of the samples of interest can deviate for these of the positive controls.

These thresholds are used to determine if regions are duplicated, deleted or occur in the normal number of copies (2) in the samples of interst. Qbase+ shows these calls in a bar chart in which the thresholds are used for coloring the bars (red for duplications, blue for deletions and grey for normal copy number). The reason why the default settings for these thresholds are:

  • 1.414: it's the geometric mean of 1 and 2 copies
  • 2.449: it's the geometric mean of 2 and 3 copies

These default settings are recommended for diploid organisms (human, mouse, rat...).

Mortasecca.png Warning: The Target bar chart also show the copy numbers, but without bar coloring