Identify QIAseq DNA Ultra Somatic Variants
The Identify QIAseq DNA Ultra Somatic Variants template workflow supports analysis of Illumina QIAseq Ultra panel data. The ultra panels are designed to provide high coverage in targeted regions to allow identification of low frequency variants in cfDNA. As the read structure is different from standard QIAseq panels, the Identify QIAseq DNA Ultra Somatic Variants template workflow should only be used to process data from from QIAseq Ultra panels.
The Identify QIAseq DNA Ultra Somatic Variants workflow is set up to detect very low frequency variants. Please note that to call low frequency variants, coverage must be high. In low coverage samples or regions, very low frequency variants are unlikely to be represented in the reads.
The primers and target regions for the Ultra panels are available in the reference data set QIAseq DNA Ultra Panels hg38.
To run the workflow go to:
Template Workflows | Biomedical Workflows (
) | QIAseq Panel Analysis (
) | QIAseq DNA Workflows (
) | Identify QIAseq DNA Ultra Somatic Variants (Illumina) (
)
Options in the following dialogs can be configured:
- Choose where to run. If you are connected to a CLC Server via the CLC Workbench, you will be asked where you would like to run the analysis. We recommend that you run the analysis on a CLC Server when possible.
- Select Reads. Select the sequencing reads. When analyzing more than one sample at a time, check the Batch checkbox in the lower left corner of the dialog.
- Specify reference data handling. Select the relevant Reference Data Set, see Reference data management for details. QIAseq DNA Ultra Panels hg38 will be pre-selected and is recommended for running this workflow.
- Configure batching. If running the workflow in Batch mode, you will be asked to define the batch units. See https://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Running_workflows_in_batch_mode.html for details.
- Target regions. Choose the relevant target regions from the drop down list.
- Target primers. Choose the relevant target primers from the drop down list.
- Map Reads to Reference. Here, it is possible to configure masking. A custom masking track can be used, but by default, the masking track is set to GenomeReferenceConsortium_masking_hg38_no_alt_analysis_set, containing the regions defined by the Genome Reference Consortium, which serve primarily to remove false duplications, including one affecting the gene U2AF1.
- Create UMI Reads from Grouped Reads. Specify settings for UMI grouping. The QIAseq DNA Ultra data is expected to contain very large UMI groups and more PCR or sequencing errors may consequently be present in the UMIs compared to other sequencing protocols. Therefore, settings for grouping reads into UMI groups should be more relaxed than settings for standard panels. This is reflected in the default settings for Create UMI Reads from Grouped Reads in this workflow. See Create UMI Reads from Grouped Reads for details about UMI grouping using the tool Create UMI Reads from Grouped Reads.
- QC for Target Sequencing. Set the Minimum coverage parameter of the QC for Target Sequencing tool. Using default settings, samples where 90 percent of target region positions do not meet this threshold will be flagged in the sample report generated by the workflow.
- Copy Number Variant Detection (Targeted). Specify Controls against which the coverage pattern in your sample will be compared in order to call CNVs. If you do not specify a control mapping the CNV analysis will not be carried out. Please note that if you want the CNV analysis to be done, it is important that the control mapping supplied is a meaningful control for the sample being analyzed. Mapping of control samples for the CNV analysis can be done using the workflows described in Create QIAseq DNA CNV Control Mapping. A meaningful control must satisfy two conditions: (1) It must have a copy number status that is meaningful to compare against. For panels with targets on the X and Y chromosomes, the control and sample should be matched for gender. (2) The control read mapping must result from the same type of processing that will be applied to the sample. For more information about CNV detection see https://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Copy_Number_Variant_Detection.html.
- Create Sample Report. Specify QC items for assessment and subsequent flagging in the sample report generated by the workflow. For additional information, see https://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Create_Sample_Report.html.
- Variant filtering steps. A series of dialogs outlines the filtering cascade in this workflow. Note that the dialog names can start with Identify candidate variants, Remove or Define. The filtering cascade has been tuned using samples of relatively high quality and coverage to provide the best possible sensitivity and precision. Additional filtering may be needed, or filtering values may need to be adjusted, when working with low quality/coverage samples or when seeking a different balance between sensitivity and precision. See https://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Filter_on_Custom_Criteria.html for details on how to adjust the options.
- Remove False Positives. Set the minimum frequency for detected variants.
- Result handling. Choose if a workflow result metadata and/or log should be saved.
- Save location for new elements. Choose where to save the data, and press Finish to start the analysis.
Launching using the QIAseq Panel Analysis Assistant
The workflow is also available in the QIAseq Panel Analysis Assistant under Targeted DNA Ultra.
Subsections
- Output from the Identify QIAseq DNA Ultra Somatic Variants template workflow
- Create QIAseq DNA Ultra CNV Control Mapping
- Output from the Create QIAseq DNA Ultra CNV Control Mapping template workflow