As comprehensive genomic profiling (CGP) becomes the standard in cancer variant analysis, the scale and complexity of next-generation sequencing (NGS) data continue to grow. It is now commonplace to report on small variants, larger amplifications and deletions, various complex structural variants (fusions or breakends) as well as genomic signatures like microsatellite instability (MSI) and tumor mutation burden (TMB). Interpreting this data efficiently requires more than just a robust analysis platform — it demands flexible workflows that can be automated and that can adapt to multiple input data types and clinical needs.

VarSeq’s Custom Scripting

In our recent webcast Automate, Import, & Interpret: Using Custom Scripts in VSClinical, we explored how VarSeq’s custom scripting capabilities can be leveraged to automate complex genomic workflows.

We covered: 

• Automation strategies for CGP and other analysis pipelines.
• Examples for customizing and implementing JavaScript-based evaluation scripts.
• Scripting capabilities for importing legacy data and complex genomic results.

In this blog post I want to highlight our custom scripting capabilities for evaluating and importing structural variant (SV) calls.

VSClinical hosts built in javascript based evaluation scripts for direct import of structural variant calls from the TSO500, Archer and IonTorrent pipelines enabling users to bring this data directly into a clinical evaluation. Labs working with data from other fusion detection tools may face challenges with getting their data in the right format for import and evaluation, as a specific VCF format is usually preferred but not always available. This problem diminishes greatly when using VSClinical’s custom evaluation script architecture. Users can automate the direct import of SV calls, parse gene fusion genomic positions, account for supporting read metrics and more in the VSClinical variant interpretation suite.

Streamlining Structural Variant Evaluation with VSClinical

VSClinical affords users the flexibility to pull in their SV data based on the fields contained in their input file, enabling them to dynamically include only those that meet certain criteria for reporting. For example, users can deploy an evaluation script to import only fusions with MAPQ above a certain threshold to ensure confident alignments, or filtering out SVs with UNIQ.FRAGs below a specific threshold to remove poorly supported events from SV calls are produced by callers like STAR-Fusion, Ion Reporter, or other custom SV detection pipelines. Furthermore in an extension of VSClinical’s evaluation framework, users can leverage evaluation scripts to implement lab-specific rules for variant interpretation and reporting decisions — automating what would otherwise be time-consuming manual review.

Whether you’re operating in a high-throughput oncology lab or integrating legacy SV data into your clinical pipeline, VarSeq’s scripting support gives you more control over the flexibility and customizability of your bioinformatic workflow from evaluation to reporting.

If you missed our webcast on the topic, you can still watch it on demand here and of course please reach out to [email protected] with any questions, comments or concerns on this topic.