Pharmacogenomic (PGx) analysis empowers researchers and clinicians to tailor drug therapies based on a patient’s genetic profile, but not all regions of the genome are easy to interpret. Genes like CYP2D6 and HLA-A are tricky when it comes to rendering diplotype calls. This is due to a number of factors including high polymorphism, structural variations (including copy number variants), and pseudogene homology. Fortunately, VarSeq provides multiple flexible paths to incorporate accurate diplotype calls into your PGx workflow, either by calling them directly within the software or by importing them from external tools.

Native Copy Number Support for CYP2D6 via CYPCaller

For users working with whole genome sequencing (WGS) data, VarSeq includes a specialized algorithm called CYPCaller. This caller is optimized for CYP2D6 and leverages BAM or CRAM files to detect structural variants and calculate gene copy number. CYPCaller outputs star allele diplotypes (e.g., CYP2D6 *1/*5), which can be used directly in your PGx project without any additional annotation. These results can also be exported into a manifest format and uploaded into VarSeq, as described in our next section.

External PGx Calls? No Problem.

In addition to native calling, VarSeq also supports the import of externally generated diplotypes using a simple text-based manifest. Some of our users will leverage third party tools like OptiType or xHLA to call challenging genes such as HLA-A. They may also have a dedicated pipeline for structural variants that renders diplotype calls. The good news is, you can easily map those results into VarSeq’s PGx algorithm for comprehensive gene-drug interpretation.

To use this method, diplotypes are provided in a comma-separated format in your manifest file, such as:

A few important formatting tips:

• Include a space between the gene name and the allele (e.g., CYP2D6 *1/*5)
• Use a slash to separate alleles (*1/*5)
• Separate diplotypes with a comma and space for clarity

This manifest is then uploaded to the PGx VarSeq module. This approach ensures that even variants from hard-to-call regions are represented accurately in the final PGx report.

The bottom line is, whether you’re calling PGx genes like CYP2D6 natively using VarSeq’s CYPCaller, or integrating diplotypes from external tools, VarSeq makes it easy to update the PGx algorithm and generate accurate, actionable gene-drug recommendations.

Do you have questions about building your manifest or optimizing your pipeline? Please email [email protected], and our team will be happy to help you tailor a solution to your lab’s needs.