Fastq to Germline Variants (WES)
The Fastq to Germline Variants (WES) template workflow identifies and annotates germline variants and generates various QC metrics. It is intended for analysis of data generated with target enrichment, including whole exome sequencing (WES) data, and therefore requires target regions to be provided.
Fastq to Germline Variants (WES) can be found at:
Template Workflows | LightSpeed Workflows (
) | Fastq to Germline Variants (WES) (
)
Options in the following dialogs can be configured:
- Choose where to run If you are connected to a CLC Server via your 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 Target regions Specify target regions for analysis.
- Specify reference data handling Select a Reference Data Set. If you have not downloaded the Reference Data Set yet, the dialog will suggest the relevant data set and offer the opportunity to download it using the Download to Workbench button. If none of the available reference data sets are appropriate, custom reference data sets can be created, see https://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Reference_Data_Sets_defining_Custom_Sets.html.
- LightSpeed Fastq to Germline Variants
Specify options for the LightSpeed Fastq to Germline Variants tool:
- Reads (fastq) Press Browse to select fastq files for analysis.
- Masking mode To enable reference masking when mapping reads, set this option and select a masking track.
- Masking track Provide a masking track for the chosen reference genome if reference masking has been enabled.
- Discard duplicate mapped reads Duplicate mapped reads are per default replaced with a consensus read. Untick if duplicate mapped reads should be retained. See Deduplication for additional details.
- Minimum average quality Specify the minimum average quality of detected variants. See Germline variant detection for additional details.
- Lenient inversion detection Enable lenient inversion detection to allow detection of inversions which only has read support in one direction on each of the breakpoints. Enabling this option can increase processing time and can result in detection of more false positive inversions.
- Minimum allele count Specify the minimum number of reads supporting an identified variant.
- Batch Select if fastq files from different samples are used as input, and each sample should be analyzed individually (for information about batching see Batching).
- Join lanes when batching Select to join fastq files from the same sample that were sequenced on different lanes.
- QC for Targeted Sequencing Set the Minimum coverage parameter of the QC for Targeted 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 Fastq to Germline CNV Control. 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 Select relevant summary items and specify thresholds for quality control. Summary items, thresholds and an indication of whether specified thresholds were met, will be shown in the quality control section of the sample report. The default summary items are appropriate for many data sets, but may need to be adjusted. For additional information, see https://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=Create_Sample_Report.html.
- 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.
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