• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

癌症 SIGVAR:一种用于种系变异的遗传性癌症相关基因的半自动解释工具。

Cancer SIGVAR: A semiautomated interpretation tool for germline variants of hereditary cancer-related genes.

机构信息

BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, WuHan, China.

BGI Genomics, BGI-Shenzhen, ShenZhen, China.

出版信息

Hum Mutat. 2021 Apr;42(4):359-372. doi: 10.1002/humu.24177. Epub 2021 Mar 6.

DOI:10.1002/humu.24177
PMID:33565189
Abstract

Cancer is one of the most important health issues globally and the accuracy of interpretation of cancer-related variants is critical for the clinical management of hereditary cancer. ClinGen Sequence Variant Interpretation Working Groups have developed many adaptations of American College of Medical Genetics and Genomics and the Association of Molecular Pathologists guidelines to improve the consistency of interpretation. We combined the most recent adaptations to expand the number of the criteria from 28 to 48 and developed a tool called Cancer SIGVAR to help genetic counselors interpret the clinical significance of cancer germline variants. Our tool can accept VCF files as input and realize fully automated interpretation based on 21 criteria and semiautomated interpretation based on 48 criteria. We validated the performance of our tool with the ClinVar and CLINVITAE benchmark databases, achieving an average consistency for pathogenic and benign assessment up to 93.71% and 79.38%, respectively. We compared Cancer SIGVAR with two similar tools, InterVar and PathoMAN, and analyzed the main differences in criteria and implementation. Furthermore, we selected 911 variants from another two in-house benchmark databases, and semiautomated interpretation reached an average classification consistency of 98.35%. Our findings highlight the need to optimize automated interpretation tools based on constantly updated guidelines. Cancer SIGVAR is publicly available at http://cancersigvar.bgi.com/.

摘要

癌症是全球最重要的健康问题之一,准确解读与癌症相关的变异对于遗传性癌症的临床管理至关重要。ClinGen 序列变异解释工作组已经对美国医学遗传学与基因组学学院和分子病理学家协会的指南进行了许多改编,以提高解释的一致性。我们结合了最新的改编版本,将标准数量从 28 个扩展到 48 个,并开发了一个名为 Cancer SIGVAR 的工具,帮助遗传咨询师解读癌症种系变异的临床意义。我们的工具可以接受 VCF 文件作为输入,并根据 21 个标准实现完全自动化解释,根据 48 个标准实现半自动解释。我们使用 ClinVar 和 CLINVITAE 基准数据库验证了我们工具的性能,致病性和良性评估的平均一致性分别达到 93.71%和 79.38%。我们将 Cancer SIGVAR 与两个类似的工具 InterVar 和 PathoMAN 进行了比较,并分析了标准和实现方面的主要差异。此外,我们从另外两个内部基准数据库中选择了 911 个变体,半自动解释达到了 98.35%的平均分类一致性。我们的研究结果强调了需要根据不断更新的指南优化自动化解释工具。Cancer SIGVAR 可在 http://cancersigvar.bgi.com/ 上公开获取。

相似文献

1
Cancer SIGVAR: A semiautomated interpretation tool for germline variants of hereditary cancer-related genes.癌症 SIGVAR:一种用于种系变异的遗传性癌症相关基因的半自动解释工具。
Hum Mutat. 2021 Apr;42(4):359-372. doi: 10.1002/humu.24177. Epub 2021 Mar 6.
2
InterVar: Clinical Interpretation of Genetic Variants by the 2015 ACMG-AMP Guidelines.InterVar:依据2015年美国医学遗传学与基因组学学会(ACMG)-分子病理学协会(AMP)指南对基因变异进行临床解读
Am J Hum Genet. 2017 Feb 2;100(2):267-280. doi: 10.1016/j.ajhg.2017.01.004. Epub 2017 Jan 26.
3
vaRHC: an R package for semi-automation of variant classification in hereditary cancer genes according to ACMG/AMP and gene-specific ClinGen guidelines.vaRHC:一个用于根据 ACMG/AMP 和基因特异性 ClinGen 指南半自动分类遗传性癌症基因变异的 R 包。
Bioinformatics. 2023 Mar 1;39(3). doi: 10.1093/bioinformatics/btad128.
4
Specifications of the ACMG/AMP Variant Classification Guidelines for Germline Variant Curation.ACMG/AMP 变异分类指南用于种系变异的临床解释:规范
Hum Mutat. 2023;2023. doi: 10.1155/2023/9537832. Epub 2023 Mar 29.
5
VIP-HL: Semi-automated ACMG/AMP variant interpretation platform for genetic hearing loss.VIP-HL:用于遗传性听力损失的半自动 ACMG/AMP 变异解释平台。
Hum Mutat. 2021 Dec;42(12):1567-1575. doi: 10.1002/humu.24277. Epub 2021 Sep 2.
6
Variant Classification for Pompe disease; ACMG/AMP specifications from the ClinGen Lysosomal Diseases Variant Curation Expert Panel.庞贝病变异分类;ClinGen 溶酶体疾病变异临床解读专家小组的 ACMG/AMP 规范。
Mol Genet Metab. 2023 Sep-Oct;140(1-2):107715. doi: 10.1016/j.ymgme.2023.107715. Epub 2023 Oct 26.
7
Specifications of the ACMG/AMP variant curation guidelines for the analysis of germline CDH1 sequence variants.ACMG/AMP 变体解读指南用于分析种系 CDH1 序列变异的规范。
Hum Mutat. 2018 Nov;39(11):1553-1568. doi: 10.1002/humu.23650.
8
Variant Interpretation for Cancer (VIC): a computational tool for assessing clinical impacts of somatic variants.变体解读癌症工具(VIC):一个用于评估体细胞变异临床影响的计算工具。
Genome Med. 2019 Aug 23;11(1):53. doi: 10.1186/s13073-019-0664-4.
9
Toward automation of germline variant curation in clinical cancer genetics.朝着临床肿瘤遗传学中种系变异体管理的自动化迈进。
Genet Med. 2019 Sep;21(9):2116-2125. doi: 10.1038/s41436-019-0463-8. Epub 2019 Feb 21.
10
Clinical Interpretation of Sequence Variants.序列变异的临床解读。
Curr Protoc Hum Genet. 2020 Jun;106(1):e98. doi: 10.1002/cphg.98.

引用本文的文献

1
HerediVar and HerediClassify: tools for streamlining genetic variant classification in hereditary breast and ovarian cancer.HerediVar和HerediClassify:用于简化遗传性乳腺癌和卵巢癌基因变异分类的工具。
Hum Genomics. 2025 Jul 4;19(1):76. doi: 10.1186/s40246-025-00787-w.
2
Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors.变异影响预测器数据库(VIPdb),版本 2:三十年来遗传变异影响预测器的趋势。
Hum Genomics. 2024 Aug 28;18(1):90. doi: 10.1186/s40246-024-00663-z.
3
Variant Impact Predictor database (VIPdb), version 2: Trends from 25 years of genetic variant impact predictors.
变异影响预测数据库(VIPdb),版本2:25年基因变异影响预测的趋势
bioRxiv. 2024 Jun 28:2024.06.25.600283. doi: 10.1101/2024.06.25.600283.
4
Mutation characteristics of cancer susceptibility genes in Chinese ovarian cancer patients.中国卵巢癌患者中癌症易感基因的突变特征
Front Oncol. 2024 May 16;14:1395818. doi: 10.3389/fonc.2024.1395818. eCollection 2024.
5
Identification of pathogenic germline variants in a large Chinese lung cancer cohort by clinical sequencing.通过临床测序鉴定大型中国肺癌队列中的致病性种系变异。
Mol Oncol. 2024 May;18(5):1301-1315. doi: 10.1002/1878-0261.13548. Epub 2024 Jan 25.
6
vaRHC: an R package for semi-automation of variant classification in hereditary cancer genes according to ACMG/AMP and gene-specific ClinGen guidelines.vaRHC:一个用于根据 ACMG/AMP 和基因特异性 ClinGen 指南半自动分类遗传性癌症基因变异的 R 包。
Bioinformatics. 2023 Mar 1;39(3). doi: 10.1093/bioinformatics/btad128.
7
MARGINAL: An Automatic Classification of Variants in and Genes Using a Machine Learning Model.边缘:使用机器学习模型对 和 基因中的变异进行自动分类。
Biomolecules. 2022 Oct 24;12(11):1552. doi: 10.3390/biom12111552.
8
Towards Next-Generation Sequencing (NGS)-Based Newborn Screening: A Technical Study to Prepare for the Challenges Ahead.迈向基于下一代测序(NGS)的新生儿筛查:为应对未来挑战做准备的技术研究。
Int J Neonatal Screen. 2022 Feb 24;8(1):17. doi: 10.3390/ijns8010017.