Whole genome sequencing is rapidly evolving, but accurate variant detection—especially in complex genomic regions—remains a major challenge.

In this webinar, we will explore how pangenome-informed, AI-driven variant calling using Google DeepVariant enables more accurate and comprehensive detection of genomic variants with DNBSEQ-T7+. We will also highlight how DNBSEQ-T7+ delivers higher accuracy compared to other leading platforms.

By combining deep learning models with pangenome graph-based alignment, this approach significantly improves variant-calling performance in challenging regions such as homopolymers, segmental duplications, and structurally complex loci.

What you will learn:

  • How pangenome-informed DeepVariant improves germline variant calling accuracy
  • The role of AI (deep learning) in modern variant detection workflows
  • Performance gains of DNBSEQ-T7+ in complex regions, including homopolymers, segmental duplications, and Copy Number Variants (CNV) regions.
  • Case studies demonstrating improved detection in challenging loci, such as histone clusters and X-transposed regions

Agenda:

Scaling $100 Genome: Maximizing Throughput and Accuracy on DNBSEQ-T7+

Drew Kebbel, Technical Sales Manager, Complete Genomics
Duration: 10 minutes

High-Accuracy Variant Calling Using Pangenome-Informed, AI-Driven Deep Variant on DNBSEQ-T7+

Andrew Carrol, Product Lead – Genomics, Google AI
Duration: 30 minutes

Q&A

Duration: 20 minutes

Register Here