Abstract
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 makes DeepVariant a universal variant calling solution for long-read sequencing platforms.
Competing Interest Statement
A.K., P.C., K.S., D.C., M.N., A.C. are employees of Google LLC and own Alphabet stock as part of the standard compensation package. E.A. is the founder of Personalis Inc and Deepcell Inc., advisor Pacific Biosciences, SequenceBio. E.A.A. has received support in kind Illumina, Oxford Nanopore, Pacific Biosciences. Stockholder Pacific Biosciences, Oxford Nanopore. K.H.M. is a science advisory board member of Centaura; K.H.M. has received travel funds to speak at events hosted by Oxford Nanopore Technologies. J.G. holds stock in ONT and PacBIo. J.G., K.S. and S.G. has accepted bursary to attend and speak at conferences on behalf of ONT.