A crucial step in any next-generation sequencing (NGS) analysis is quality control, which is essential for confirming the validity of potentially clinically relevant findings before proceeding with any subsequent variant interpretation or reporting. While Golden Helix does not directly provide NGS validation services, our VarSeq software provides robust analysis tools that can help users perform their own quality control (QC) checks and troubleshoot unexpected results in NGS analysis. Several instances where quality control is needed include validating an NGS pipeline with a publicly available truth set or confirming the quality and validity of a pathogenic finding that was detected by a non-NGS method. This blog will cover a few tools and tips that can be leveraged in VarSeq for quality checks on your NGS analysis.
Examine the Alignment Files in GenomeBrowse
Our built-in genome browser allows you to plot BAM or CRAM files and visually inspect the sequencing reads and pile up data from a sample at any locus along the genome. This may be useful when validating a call that was made by PCR, for example, but not in your NGS analysis. If, on inspection of the variant calling file (VCF) produced by your secondary analysis, the variant is not present, a quick review of the alignment files can indicate whether there were reads present for the expected call, and whether you need to revisit or tweak your variant calling methodology. This inspection can also give you a quick representation of the coverage in a particular region. You may also be able to visually inspect for strand bias or reads that were filtered for poor quality.
Check Coverage Region Statistics
If a user wants a more detailed look at the coverage over a particular sample than the visualizations available in GenomeBrowse, we have an algorithm for that. VarSeq’s Coverage Regions algorithm provides detailed per-sample and per-region coverage metrics. This allows you to:
- Identify coverage at various depth thresholds across sequenced regions of the genome and detect where a variant might have gone undetected due to poor coverage.
- Combined with our VSClinical tool, you can set thresholds to flag or fail regions with insufficient read depth or mapping quality, and
- report coverage metrics alongside variant interpretation for complete transparency in your results.
Use Variant Flags to Track and Troubleshoot
VarSeq provides variant tracking tools that are extremely useful when managing and investigating specific variants. A user can use our variant flags to:
- Mark pathogenic variants they expect to identify for reporting based on orthogonal methods or prior knowledge.
- Track whether a given filtering strategy is too strict.
- Isolate variants that pass or fail at various stages in the filtering pipeline.
By flagging variants, you can easily trace whether they were excluded due to a specific filtering parameter or quality threshold.
Looking for more tips? Reach out to our team at [email protected] or ask about our tutorials on setting up custom flags, interpreting coverage metrics, and using GenomeBrowse.
