杂交基因组组装
生物
深度测序
Illumina染料测序
遗传学
DNA测序
基因分型
结构变异
计算生物学
基因
基因组
大规模并行测序
DNA
参考基因组
基因型
作者
Ahmed Alkanaq,Kohei Hamanaka,Futoshi Sekiguchi,Masataka Taguri,Atsushi Takata,Noriko Miyake,Satoko Miyatake,Takeshi Mizuguchi,Naomichi Matsumoto
标识
DOI:10.1038/s10038-019-0654-9
摘要
The recent advent of long-read sequencing technologies is expected to provide reasonable answers to genetic challenges unresolvable by short-read sequencing, primarily the inability to accurately study structural variations, copy number variations, and homologous repeats in complex parts of the genome. However, long-read sequencing comes along with higher rates of random short deletions and insertions, and single nucleotide errors. The relatively higher sequencing accuracy of short-read sequencing has kept it as the first choice of screening for single nucleotide variants and short deletions and insertions. Albeit, short-read sequencing still suffers from systematic errors that tend to occur at specific positions where a high depth of reads is not always capable to correct for these errors. In this study, we compared the genotyping of mitochondrial DNA variants in three samples using PacBio's Sequel (Pacific Biosciences Inc., Menlo Park, CA, USA) long-read sequencing and illumina's HiSeqX10 (illumine Inc., San Diego, CA, USA) short-read sequencing data. We concluded that, despite the differences in the type and frequency of errors in the long-reads sequencing, its accuracy is still comparable to that of short-reads for genotyping short nuclear variants; due to the randomness of errors in long reads, a lower coverage, around 37 reads, can be sufficient to correct for these random errors.
科研通智能强力驱动
Strongly Powered by AbleSci AI