Identify Somatic Variants from Tumor Normal Pair (WGS)

The Identify Somatic Variants from Tumor Normal Pair (WGS) ready-to-use workflow can be used to identify potential somatic variants in a tumor sample when you also have a normal/control sample from the same subject.

When running this workflow the reads are mapped and the variants identified. An internal workflow removes germline variants that are found in the mapped reads of the normal/control sample and variants outside the target region are removed as they are likely to be false positives due to non-specific mapping of sequencing reads. Next, remaining variants are annotated with gene names, amino acid changes, conservation scores and information from relevant databases like ClinVar (variants with clinically relevant association). Finally, information from dbSNP is added to see which of the detected variants have been observed before and which are completely new.

Run the Identify Somatic Variants from Tumor Normal Pair (WGS) workflow

To run the Identify Somatic Variants from Tumor Normal Pair (WGS) tool, go to:

        Toolbox | Ready-to-Use Workflows | Whole Genome Sequencing (Image whole_genome_folder_closed_16_n_p) | Somatic Cancer (Image somatic_folder_closed_16_n_p) | Identify Somatic Variants from Tumor Normal Pair (WGS) (Image filter_somatic_var_wgs_16_n_p)

  1. Go to the toolbox and double-click on the Identify Somatic Variants from Tumor Normal Pair (WGS) ready-to-use workflow.

  2. First (figure 16.19), select the tumor sample reads.

    Image filter_somatic_variants_from_tumor_normal_step1_wgs
    Figure 16.19: Select the tumor sample reads.

  3. In the next wizard step, specify the normal sample reads.

  4. In the next dialog, select which data set should be used to identify variants (figure 16.20).

    Image identify_somatic_variants_wgs
    Figure 16.20: Choose the relevant reference Data Set to identify variants.

  5. In the next wizard step you can adjust the settings used for variant detection (figure 16.21).

    Image filter_somatic_variants_from_tumor_normal_step5_wgs
    Figure 16.21: Specify the settings for the variant detection.

    For a description of the different parameters that can be adjusted, see http://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Low_Frequency_Variant_Detection.html. If you click on "Locked Settings", you will be able to see all parameters used for variant detection in the ready-to-use workflow.

  6. In the Remove Variants Present in Control Reads step, you can adjust the settings for removal of germline variants (figure 16.22).

    Image filter_somatic_variants_from_tumor_normal_step6_wgs
    Figure 16.22: Specify setting for removal of germline variants.

  7. In the last wizard step you can check the selected settings by clicking on the button labeled Preview All Parameters. In the Preview All Parameters wizard you can only check the settings, and if you wish to make changes you have to use the Previous button from the wizard to edit parameters in the relevant windows.

  8. Choose to Save your results and click Finish.

Output from the Identify Somatic Variants from Tumor Normal Pair (WGS) workflow

The following outputs are generated:

  1. Read Mapping Tumor (Image read_track_16_n_p) The mapped sequencing reads for the tumor sample. The reads are shown in different colors depending on their orientation, whether they are single reads or paired reads, and whether they map unambiguously (see http://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Coloring_mapped_reads.html).
  2. Read Mapping Normal (Image read_track_16_n_p) The mapped sequencing reads for the normal sample. The reads are shown in different colors depending on their orientation, whether they are single reads or paired reads, and whether they map unambiguously.
  3. Mapping Report Tumor (Image proteinreport_16_n_p) The report consists of a number of tables and graphs that in different ways provide information about the mapped reads from the tumor sample.
  4. Mapping Report Normal (Image proteinreport_16_n_p) The report consists of a number of tables and graphs that in different ways provide information about the mapped reads from the normal sample.
  5. Amino Acids Changes Track that shows the consequences of the variants at the amino acid level in the context of the original amino acid sequence. A variant introducing a stop mutation is illustrated with a red amino acid.
  6. Annotated Somatic Variants (Image variant_track_16_n_p) A variant track holding the identified and annotated somatic variants. The variants can be shown in track format or in table format. When holding the mouse over the detected variants in the Track List, a tooltip appears with information about the individual variants. You will have to zoom in on the variants to be able to see the detailed tooltip.
  7. Track List Tumor Normal Comparison (Image trackset_16_n_p) A collection of tracks presented together. Shows the annotated variant track together with the human reference sequence, genes, transcripts, coding regions, the mapped reads for both normal and tumor, the annotated somatic variants, information from the ClinVar database, and finally a track showing the conservation score (see figure 16.23).

Image identify_somatic_variants_genomebrowserview_wgs
Figure 16.23: The Track List presents all the different data tracks together and makes it easy to compare different tracks.