Bionano Genomics, Inc. announced significant upgrades to its suite of computational tools for comprehensive cancer analysis. These advancements to the company?s VIA? software solution enhance the detection and interpretation of aneusomies, and improve the analysis, visualization, interpretation, and reporting of data types including optical genome mapping (OGM), next generation sequencing, and microarray, for comprehensive assessment of hematological diseases.

Advancements to the suite of tools include: Enhanced Detection of Critical Variants: Improved sensitivity and precision provide increased accuracy for detection of aneusomies with variant allele fractions (VAFs) as low as 5%, with sensitivities and positive predictive values of 95% or greater and Increased ability to detect small structural variants (SVs) at low allele fractions through a reference-guided approach in a new pipeline to detect novel SVs from OGM data. Automated Analysis and Interpretation of Variants: Enhancements to automated SV classification include critical SV data such as quality, frequency and size to more accurately identify disease-relevant SVs, making analysis and interpretation faster and more efficient; A new standardized Phred scale calculation for SV confidence scores aligns with industry standards and simplifies the identification of high-quality variants, instilling confidence in users for variant calls; New copy number variant (CNV) dual analysis completes the variant analysis pipeline and enables residual disease assessment with the ability to differentiate new emergent variants from original variants. Dynamic Visualization for Better Representation of Findings: Upgraded Circos plot visualization offers a comprehensive view of the genomic landscape, promoting clear and accurate interpretation of datasets and differentiation between simple and complex genomes; Customized and automated reporting options offer the ability to include Circos plots, whole genome plots and ideograms for a faster and more complete visual representation of SVs relevant to sample analysis.