纳米孔测序
索引
可扩展性
计算机科学
计算生物学
协议(科学)
基因组学
DNA测序
基因组
1000基因组计划
参考基因组
结构变异
生物
遗传学
单核苷酸多态性
基因
数据库
医学
基因型
病理
替代医学
作者
Mikhail Kolmogorov,Kimberley Billingsley,Mira Mastoras,Melissa Meredith,Jean Monlong,Ryan Lorig-Roach,Mobin Asri,Pilar Álvarez Jerez,Laksh Malik,Ramita Dewan,Xylena Reed,Rylee Genner,Kensuke Daida,Sairam Behera,Kishwar Shafin,Trevor Pesout,Jeshuwin Prabakaran,P. Carnevali,Jianzhi Yang,Arang Rhie
标识
DOI:10.1101/2023.01.12.523790
摘要
Long-read sequencing technologies substantially overcome the limitations of short-reads but to date have not been considered as feasible replacement at scale due to a combination of being too expensive, not scalable enough, or too error-prone. Here, we develop an efficient and scalable wet lab and computational protocol for Oxford Nanopore Technologies (ONT) long-read sequencing that seeks to provide a genuine alternative to short-reads for large-scale genomics projects. We applied our protocol to cell lines and brain tissue samples as part of a pilot project for the NIH Center for Alzheimer's and Related Dementias (CARD). Using a single PromethION flow cell, we can detect SNPs with F1-score better than Illumina short-read sequencing. Small indel calling remains to be difficult inside homopolymers and tandem repeats, but is comparable to Illumina calls elsewhere. Further, we can discover structural variants with F1-score comparable to state-of the-art methods involving Pacific Biosciences HiFi sequencing and trio information (but at a lower cost and greater throughput). Using ONT based phasing, we can then combine and phase small and structural variants at megabase scales. Our protocol also produces highly accurate, haplotype-specific methylation calls. Overall, this makes large-scale long-read sequencing projects feasible; the protocol is currently being used to sequence thousands of brain-based genomes as a part of the NIH CARD initiative. We provide the protocol and software as open-source integrated pipelines for generating phased variant calls and assemblies.
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