ReSeq模拟真实的Illumina高通量测序数据。

IF 12.3 1区 生物学 Q1 Agricultural and Biological Sciences Genome Biology Pub Date : 2021-02-19 DOI:10.1186/s13059-021-02265-7
Stephan Schmeing, Mark D Robinson
{"title":"ReSeq模拟真实的Illumina高通量测序数据。","authors":"Stephan Schmeing,&nbsp;Mark D Robinson","doi":"10.1186/s13059-021-02265-7","DOIUrl":null,"url":null,"abstract":"<p><p>In high-throughput sequencing data, performance comparisons between computational tools are essential for making informed decisions at each step of a project. Simulations are a critical part of method comparisons, but for standard Illumina sequencing of genomic DNA, they are often oversimplified, which leads to optimistic results for most tools. ReSeq improves the authenticity of synthetic data by extracting and reproducing key components from real data. Major advancements are the inclusion of systematic errors, a fragment-based coverage model and sampling-matrix estimates based on two-dimensional margins. These improvements lead to more faithful performance evaluations. ReSeq is available at https://github.com/schmeing/ReSeq .</p>","PeriodicalId":48922,"journal":{"name":"Genome Biology","volume":"22 1","pages":"67"},"PeriodicalIF":12.3000,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13059-021-02265-7","citationCount":"5","resultStr":"{\"title\":\"ReSeq simulates realistic Illumina high-throughput sequencing data.\",\"authors\":\"Stephan Schmeing,&nbsp;Mark D Robinson\",\"doi\":\"10.1186/s13059-021-02265-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In high-throughput sequencing data, performance comparisons between computational tools are essential for making informed decisions at each step of a project. Simulations are a critical part of method comparisons, but for standard Illumina sequencing of genomic DNA, they are often oversimplified, which leads to optimistic results for most tools. ReSeq improves the authenticity of synthetic data by extracting and reproducing key components from real data. Major advancements are the inclusion of systematic errors, a fragment-based coverage model and sampling-matrix estimates based on two-dimensional margins. These improvements lead to more faithful performance evaluations. ReSeq is available at https://github.com/schmeing/ReSeq .</p>\",\"PeriodicalId\":48922,\"journal\":{\"name\":\"Genome Biology\",\"volume\":\"22 1\",\"pages\":\"67\"},\"PeriodicalIF\":12.3000,\"publicationDate\":\"2021-02-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1186/s13059-021-02265-7\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genome Biology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1186/s13059-021-02265-7\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Agricultural and Biological Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genome Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1186/s13059-021-02265-7","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 5

摘要

在高通量测序数据中,计算工具之间的性能比较对于在项目的每个步骤中做出明智的决策至关重要。模拟是方法比较的关键部分,但对于基因组DNA的标准Illumina测序,它们通常过于简化,这导致大多数工具的结果都很乐观。ReSeq通过从真实数据中提取和再现关键组件来提高合成数据的真实性。主要的进步是包含了系统误差、基于片段的覆盖模型和基于二维边缘的抽样矩阵估计。这些改进导致更可靠的性能评估。ReSeq可在https://github.com/schmeing/ReSeq上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

摘要图片

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
ReSeq simulates realistic Illumina high-throughput sequencing data.

In high-throughput sequencing data, performance comparisons between computational tools are essential for making informed decisions at each step of a project. Simulations are a critical part of method comparisons, but for standard Illumina sequencing of genomic DNA, they are often oversimplified, which leads to optimistic results for most tools. ReSeq improves the authenticity of synthetic data by extracting and reproducing key components from real data. Major advancements are the inclusion of systematic errors, a fragment-based coverage model and sampling-matrix estimates based on two-dimensional margins. These improvements lead to more faithful performance evaluations. ReSeq is available at https://github.com/schmeing/ReSeq .

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Genome Biology
Genome Biology BIOTECHNOLOGY & APPLIED MICROBIOLOGY-GENETICS & HEREDITY
CiteScore
25.50
自引率
3.30%
发文量
0
审稿时长
14 weeks
期刊介绍: Genome Biology is a leading research journal that focuses on the study of biology and biomedicine from a genomic and post-genomic standpoint. The journal consistently publishes outstanding research across various areas within these fields. With an impressive impact factor of 12.3 (2022), Genome Biology has earned its place as the 3rd highest-ranked research journal in the Genetics and Heredity category, according to Thomson Reuters. Additionally, it is ranked 2nd among research journals in the Biotechnology and Applied Microbiology category. It is important to note that Genome Biology is the top-ranking open access journal in this category. In summary, Genome Biology sets a high standard for scientific publications in the field, showcasing cutting-edge research and earning recognition among its peers.
期刊最新文献
Cohesin distribution alone predicts chromatin organization in yeast via conserved-current loop extrusion. DeepKINET: a deep generative model for estimating single-cell RNA splicing and degradation rates. Seqrutinator: scrutiny of large protein superfamily sequence datasets for the identification and elimination of non-functional homologues. Systemic interindividual DNA methylation variants in cattle share major hallmarks with those in humans. TaqTth-hpRNA: a novel compact RNA-targeting tool for specific silencing of pathogenic mRNA.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1