Login / Signup

Local read haplotagging enables accurate long-read small variant calling.

Alexey KolesnikovDaniel CookMaria NattestadLucas BrambrinkBrandy McNultyJohn E GorzynskiSneha GoenkaEuan A AshleyMiten JainKaren H MigaBenedict PatenPi-Chuan ChangAndrew CarrollKishwar Shafin
Published in: Nature communications (2024)
Long-read sequencing technology has enabled variant detection in difficult-to-map regions of the genome and enabled rapid genetic diagnosis in clinical settings. Rapidly evolving third-generation sequencing platforms like Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) are introducing newer platforms and data types. It has been demonstrated that variant calling methods based on deep neural networks can use local haplotyping information with long-reads to improve the genotyping accuracy. However, using local haplotype information creates an overhead as variant calling needs to be performed multiple times which ultimately makes it difficult to extend to new data types and platforms as they get introduced. In this work, we have developed a local haplotype approximate method that enables state-of-the-art variant calling performance with multiple sequencing platforms including PacBio Revio system, ONT R10.4 simplex and duplex data. This addition of local haplotype approximation simplifies long-read variant calling with DeepVariant.
Keyphrases
  • single molecule
  • electronic health record
  • single cell
  • genome wide
  • neural network
  • big data
  • gene expression
  • loop mediated isothermal amplification
  • high throughput
  • social media
  • machine learning
  • real time pcr