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bioRxiv · 10.1101/2019.12.29.890418

NanoCaller for accurate detection of SNPs and small indels from long-read sequencing by deep neural networks

Ahsan, U.·Liu, Q.·Wang, K.
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Abstract

Long-read sequencing enables variant detection in genomic regions that are considered difficult-to-map by short-read sequencing. To fully exploit the benefits of longer reads, here we present a deep-learning method NanoCaller, which detects SNPs using long-range haplotype information, then phases long reads with called SNPs and calls indels with local realignment. Evaluation on 8 human genomes demonstrated that NanoCaller generally achieves better performance than competing approaches. We experimentally validated 41 novel variants in a widely-used benchmarking genome, which cannot be reliably detected previously. In summary, NanoCaller facilitates the discovery of novel variants in complex genomic regions from long- read sequencing.

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Ahsan, U., Liu, Q., Wang, K.. 2019-12-30. NanoCaller for accurate detection of SNPs and small indels from long-read sequencing by deep neural networks. https://doi.org/10.1101/2019.12.29.890418

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