I am pleased to announce that VarSeq 2.6.2 is now available! VarSeq 2.6.2 comes jammed-packed with new features and capabilities to advance your NGS analysis workflows. In this blog, I will describe the major changes to the VSPGx workflow, which were the main focus of the release, and I will also talk about other exciting features and new algorithms that come with VarSeq 2.6.2.

Let’s start with how VS 2.6.2 enhances your pharmacogenomic analysis. In 2.6.2, VSPGx has enhanced capabilities to support analyzing pharmacogenes that are historically difficult to handle. Namely, we have created a specialized CYP2D6 star allele caller, CypCall, which accurately calls star alleles in CYP2D6 despite CYP2D6’s highly homologous paralog CYP2D7. In addition, the critical HLA gene star alleles can be integrated into VarSeq and reported, allowing for a more comprehensive reporting process.  Annotations are a critical component of every pharmacogenomic workflow, and we are proud to announce that we have expanded the annotations and reporting to include FDA-defined alleles, drugs, and recommendations, which work in tandem with CPIC guidelines. VarSeq 2.6.2 has flexible data import infrastructure, which will allow calling PGx variants from coverage BAM files and importing long read data, including variant phase information for star allele calling, ultimately strengthening and variant analysis.

Outside of the pharmacogenomics workflow, we focused on improving compound variant effect analysis. This includes analyzing variants in their complex variant state alongside the variants split into allelic privatives. This is achieved with a new import option to additionally create a complex variant table while still importing variants split into allelic privatives as recommended. A new algorithm was added that enables the detection of compound het variants with CNVs and or compound het CNVs with other CNVs.

In general, VarSeq 2.6.2 welcomes new algorithms that utilize variant phase information for variant analysis. Incorporating and accounting for variants that are in-phase or out-of-phase with one another provides important information about the compound effect of variants and their impact on disease inheritance and severity. There are two new algorithms that will use variant phase to aid in variant analysis. The first is the collapse phased variants algorithm. This algorithm will merge variants that are in phase and within a certain distance threshold. For substitutions, the variants must be within three base pairs to be merged. For length-altering variants, the distance threshold is a user-defined parameter. The purpose of this algorithm is to identify groups of variants for which the compound effect of the variants differs from the effect of any one variant on its own. Second is the phased compound het algorithm. This algorithm detects when variants are within the same gene and out-of-phase with one another, indicating that both copies of the gene are mutated and could indicate a significant reduction in gene function and a more severe phenotype.

These features were some of the most requested features from our customer base so we are very excited to finally provide these capabilities. There are many other improvements and also bug fixes that are included in VarSeq 2.6.2, so please browse through the release notes to get the full story of VarSeq 2.6.2!

If these new features are of interest to you, please contact us at [email protected] to get into contact with our Area Directors, or visit us here to submit a contact request. If you need any assistance upgrading from your current VarSeq version or if you have any questions about the release, please reach out to our FAS team at [email protected].