How to run the "Identify Known Mutations from Sample Mappings" tool

To run the "Identify Known Mutations from Sample Mappings" tool go to the toolbox:

        Toolbox | Resequencing Analysis (Image resequencing) | Identify Known Mutations from Sample Mappings (Image mutation_16_n_p)

This opens the wizard shown in figure 21.1.

Image identify_known_mutations_step1
Figure 21.1: Select the read mapping(s) to analyze.

Select the read mapping to analyze and click on the button labeled Next.

In the next wizard that appears, you get the following options:

Variant track

  • Variant track Select the variant track that contains the specific variants that you wish to test for in your read mapping (figure 21.2). Note! You can only select one variant track at the time. If you wish to compare with more than one variant track, you must run the analysis with each individual variant track at the time.

Image identify_known_mutations_step2
Figure 21.2: Select the variant track with the variants that you wish to use for variant testing. In this example we will use "Clinvar".

Detection requirements

  • Minimum coverage The minimum number of reads that covers the position of the variant, which is required to set "Sufficient Coverage" to YES.
  • Detection frequency The minimum allele frequency that is required to annotate a variant as being present in the sample. The same threshold will also be used to determine if a variant is homozygous or heterozygous. In case the most frequent alternative allele at the position of the considered variant has a frequency of less than this value, the zygosity of the considered variant will be reported as being homozygous.


  • Ignore broken pairs When ticked, reads from broken pairs are ignored. Broken pairs may arise for a number of reasons, one being erroneous mapping of the reads. In general, variants based on broken pair reads are likely to be less reliable, so ignoring them may reduce the number of spurious variants called. However, broken pairs may also arise for biological reasons (e.g. due to structural variants) and if they are ignored some true variants may go undetected.
  • Ignore non-specific matches Reads that have an equally good match elsewhere on the reference genome (these reads are colored yellow in the mapping view) can be ignored in the analysis. Whether you include these reads or not will be a tradeoff between sensitivity and specificity. Including them may lead to the prediction of transcripts that are not correct, whereas excluding them may mean that you will loose some true transcripts.
Click on the button labeled Next to go to the next wizard step (figure 21.3). At this step the output options can be adjusted.

Image identify_known_mutations_step3
Figure 21.3: Select the desired output format(s). If using the default settings, two types of output will be generated; individual tracks and overview tracks.

The output options are:

Specify where to save the results and click on the button labeled Finish.

The individual sample track

For each mapping track from a sample, one individual sample output track will be created (figure 21.4). The track provides more detailed information about each variant tested in this specific sample.

In the overview track the variant has been annotated with the following information:

In the individual track the variant has been annotated with the following information:

Image identify_known_mutations_output_track
Figure 21.4: Summary output of the variant tester tool.

At the bottom of the window it is possible to switch to a table view that lists all the mutations from the variant track that were found in your sample mapping. An example of the "Mutation Test overview" table can be seen in figure 21.5.

Image identify_known_mutations_output_table
Figure 21.5: Overview output of the "Identify Known Mutations from Sample Mappings" tool.