利用 CNAqc 计算验证来自肿瘤大样本测序的克隆和亚克隆拷贝数改变。

IF 12.3 1区 生物学 Q1 Agricultural and Biological Sciences Genome Biology Pub Date : 2024-01-31 DOI:10.1186/s13059-024-03170-5
Alice Antonello, Riccardo Bergamin, Nicola Calonaci, Jacob Househam, Salvatore Milite, Marc J Williams, Fabio Anselmi, Alberto d'Onofrio, Vasavi Sundaram, Alona Sosinsky, William C H Cross, Giulio Caravagna
{"title":"利用 CNAqc 计算验证来自肿瘤大样本测序的克隆和亚克隆拷贝数改变。","authors":"Alice Antonello, Riccardo Bergamin, Nicola Calonaci, Jacob Househam, Salvatore Milite, Marc J Williams, Fabio Anselmi, Alberto d'Onofrio, Vasavi Sundaram, Alona Sosinsky, William C H Cross, Giulio Caravagna","doi":"10.1186/s13059-024-03170-5","DOIUrl":null,"url":null,"abstract":"<p><p>Copy number alterations (CNAs) are among the most important genetic events in cancer, but their detection from sequencing data is challenging because of unknown sample purity, tumor ploidy, and general intra-tumor heterogeneity. Here, we present CNAqc, an evolution-inspired method to perform the computational validation of clonal and subclonal CNAs detected from bulk DNA sequencing. CNAqc is validated using single-cell data and simulations, is applied to over 4000 TCGA and PCAWG samples, and is incorporated into the validation process for the clinically accredited bioinformatics pipeline at Genomics England. CNAqc is designed to support automated quality control procedures for tumor somatic data validation.</p>","PeriodicalId":48922,"journal":{"name":"Genome Biology","volume":"25 1","pages":"38"},"PeriodicalIF":12.3000,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10832148/pdf/","citationCount":"0","resultStr":"{\"title\":\"Computational validation of clonal and subclonal copy number alterations from bulk tumor sequencing using CNAqc.\",\"authors\":\"Alice Antonello, Riccardo Bergamin, Nicola Calonaci, Jacob Househam, Salvatore Milite, Marc J Williams, Fabio Anselmi, Alberto d'Onofrio, Vasavi Sundaram, Alona Sosinsky, William C H Cross, Giulio Caravagna\",\"doi\":\"10.1186/s13059-024-03170-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Copy number alterations (CNAs) are among the most important genetic events in cancer, but their detection from sequencing data is challenging because of unknown sample purity, tumor ploidy, and general intra-tumor heterogeneity. Here, we present CNAqc, an evolution-inspired method to perform the computational validation of clonal and subclonal CNAs detected from bulk DNA sequencing. CNAqc is validated using single-cell data and simulations, is applied to over 4000 TCGA and PCAWG samples, and is incorporated into the validation process for the clinically accredited bioinformatics pipeline at Genomics England. CNAqc is designed to support automated quality control procedures for tumor somatic data validation.</p>\",\"PeriodicalId\":48922,\"journal\":{\"name\":\"Genome Biology\",\"volume\":\"25 1\",\"pages\":\"38\"},\"PeriodicalIF\":12.3000,\"publicationDate\":\"2024-01-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10832148/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genome Biology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1186/s13059-024-03170-5\",\"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/s13059-024-03170-5","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: 0

摘要

拷贝数改变(CNA)是癌症中最重要的遗传事件之一,但由于样本纯度、肿瘤倍性和肿瘤内异质性未知,从测序数据中检测CNA具有挑战性。在此,我们介绍一种受进化启发的方法--CNAqc,该方法可对从批量 DNA 测序中检测到的克隆和亚克隆 CNA 进行计算验证。CNAqc 利用单细胞数据和模拟进行了验证,已应用于 4000 多个 TCGA 和 PCAWG 样本,并已纳入英格兰基因组研究所临床认可的生物信息学管道的验证流程。CNAqc 设计用于支持肿瘤体细胞数据验证的自动质量控制程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Computational validation of clonal and subclonal copy number alterations from bulk tumor sequencing using CNAqc.

Copy number alterations (CNAs) are among the most important genetic events in cancer, but their detection from sequencing data is challenging because of unknown sample purity, tumor ploidy, and general intra-tumor heterogeneity. Here, we present CNAqc, an evolution-inspired method to perform the computational validation of clonal and subclonal CNAs detected from bulk DNA sequencing. CNAqc is validated using single-cell data and simulations, is applied to over 4000 TCGA and PCAWG samples, and is incorporated into the validation process for the clinically accredited bioinformatics pipeline at Genomics England. CNAqc is designed to support automated quality control procedures for tumor somatic data validation.

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