纳米孔
管道(软件)
计算机科学
基因组
纳米孔测序
边距(机器学习)
顺序装配
单倍型
参考基因组
基因分型
生物
计算生物学
基因
遗传学
纳米技术
材料科学
机器学习
转录组
基因型
基因表达
程序设计语言
作者
Kishwar Shafin,Trevor Pesout,Pi-Chuan Chang,Maria Nattestad,Alexey Kolesnikov,Sidharth Goel,Gunjan Baid,Mikhail Kolmogorov,Jordan M. Eizenga,Karen H. Miga,P. Carnevali,Miten Jain,Andrew Carroll,Benedict Paten
出处
期刊:Nature Methods
[Nature Portfolio]
日期:2021-11-01
卷期号:18 (11): 1322-1332
被引量:217
标识
DOI:10.1038/s41592-021-01299-w
摘要
Long-read sequencing has the potential to transform variant detection by reaching currently difficult-to-map regions and routinely linking together adjacent variations to enable read-based phasing. Third-generation nanopore sequence data have demonstrated a long read length, but current interpretation methods for their novel pore-based signal have unique error profiles, making accurate analysis challenging. Here, we introduce a haplotype-aware variant calling pipeline, PEPPER-Margin-DeepVariant, that produces state-of-the-art variant calling results with nanopore data. We show that our nanopore-based method outperforms the short-read-based single-nucleotide-variant identification method at the whole-genome scale and produces high-quality single-nucleotide variants in segmental duplications and low-mappability regions where short-read-based genotyping fails. We show that our pipeline can provide highly contiguous phase blocks across the genome with nanopore reads, contiguously spanning between 85% and 92% of annotated genes across six samples. We also extend PEPPER-Margin-DeepVariant to PacBio HiFi data, providing an efficient solution with superior performance over the current WhatsHap-DeepVariant standard. Finally, we demonstrate de novo assembly polishing methods that use nanopore and PacBio HiFi reads to produce diploid assemblies with high accuracy (Q35+ nanopore-polished and Q40+ PacBio HiFi-polished).
科研通智能强力驱动
Strongly Powered by AbleSci AI