• 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

相似文献

1
A public resource facilitating clinical use of genomes.一个促进基因组临床应用的公共资源。
Proc Natl Acad Sci U S A. 2012 Jul 24;109(30):11920-7. doi: 10.1073/pnas.1201904109. Epub 2012 Jul 13.
2
The Personal Genome Project Canada: findings from whole genome sequences of the inaugural 56 participants.加拿大个人基因组计划:首批 56 名参与者全基因组序列的研究结果。
CMAJ. 2018 Feb 5;190(5):E126-E136. doi: 10.1503/cmaj.171151.
3
Genome analysis and knowledge-driven variant interpretation with TGex.基因组分析和基于 TGex 的知识驱动的变异解释。
BMC Med Genomics. 2019 Dec 30;12(1):200. doi: 10.1186/s12920-019-0647-8.
4
GrabBlur--a framework to facilitate the secure exchange of whole-exome and -genome SNV data using VCF files.GrabBlur——一个使用VCF文件促进全外显子组和基因组单核苷酸变异(SNV)数据安全交换的框架。
BMC Genomics. 2014;15 Suppl 4(Suppl 4):S8. doi: 10.1186/1471-2164-15-S4-S8. Epub 2014 May 20.
5
Personal Genome Project UK (PGP-UK): a research and citizen science hybrid project in support of personalized medicine.英国个人基因组计划(PGP-UK):支持个性化医疗的研究与公民科学混合项目。
BMC Med Genomics. 2018 Nov 27;11(1):108. doi: 10.1186/s12920-018-0423-1.
6
Genetic Variations and Precision Medicine.基因变异与精准医学
Perspect Health Inf Manag. 2019 Apr 1;16(Spring):1a. eCollection 2019 Spring.
7
Variant information systems for precision oncology.精准肿瘤学的变异信息系统。
BMC Med Inform Decis Mak. 2018 Nov 21;18(1):107. doi: 10.1186/s12911-018-0665-z.
8
9
ClinGen advancing genomic data-sharing standards as a GA4GH driver project.ClinGen 推进基因组数据共享标准作为 GA4GH 的驱动项目。
Hum Mutat. 2018 Nov;39(11):1686-1689. doi: 10.1002/humu.23625.
10
Inferring the effect of genomic variation in the new era of genomics.在基因组学的新时代推断基因组变异的影响。
Hum Mutat. 2018 Jun;39(6):756-773. doi: 10.1002/humu.23427. Epub 2018 Apr 22.

引用本文的文献

1
Interlaboratory assessment of candidate reference materials for lentiviral vector copy number and integration site measurements.慢病毒载体拷贝数和整合位点测量候选参考物质的实验室间评估。
Mol Ther Methods Clin Dev. 2025 Apr 21;33(2):101472. doi: 10.1016/j.omtm.2025.101472. eCollection 2025 Jun 12.
2
GoldPolish-target: targeted long-read genome assembly polishing.GoldPolish目标:靶向长读长基因组组装优化
BMC Bioinformatics. 2025 Mar 7;26(1):78. doi: 10.1186/s12859-025-06091-7.
3
Small variant benchmark from a complete assembly of X and Y chromosomes.来自X和Y染色体完整组装的小变异基准。
Nat Commun. 2025 Jan 8;16(1):497. doi: 10.1038/s41467-024-55710-z.
4
Herpes Simplex Virus 1 Infection of Human Brain Organoids and Pancreatic Stem Cell-Islets Drives Organoid-Specific Transcripts Associated with Alzheimer's Disease and Autoimmune Diseases.单纯疱疹病毒1型感染人脑类器官和胰腺干细胞胰岛会驱动与阿尔茨海默病和自身免疫性疾病相关的类器官特异性转录本。
Cells. 2024 Nov 29;13(23):1978. doi: 10.3390/cells13231978.
5
A robust benchmark for detecting low-frequency variants in the HG002 Genome In A Bottle NIST reference material.用于检测基因组在瓶 NIST 参考材料 HG002 中低频变异的强大基准。
bioRxiv. 2024 Dec 5:2024.12.02.625685. doi: 10.1101/2024.12.02.625685.
6
Genomic reproducibility in the bioinformatics era.生物信息学时代的基因组可重复性。
Genome Biol. 2024 Aug 9;25(1):213. doi: 10.1186/s13059-024-03343-2.
7
Computational Tools to Assist in Analyzing Effects of the Gene Variation on Alpha-1 Antitrypsin (AAT).用于分析基因变异对 α-1 抗胰蛋白酶(AAT)影响的计算工具。
Genes (Basel). 2024 Mar 6;15(3):340. doi: 10.3390/genes15030340.
8
A cost-effective sequencing method for genetic studies combining high-depth whole exome and low-depth whole genome.一种用于基因研究的经济高效的测序方法,该方法结合了高深度全外显子组测序和低深度全基因组测序。
NPJ Genom Med. 2024 Feb 7;9(1):8. doi: 10.1038/s41525-024-00390-3.
9
Reliable multiplex generation of pooled induced pluripotent stem cells.可靠的诱导多能干细胞池的多重生成。
Cell Rep Methods. 2023 Sep 25;3(9):100570. doi: 10.1016/j.crmeth.2023.100570. Epub 2023 Aug 31.
10
Modeling of mitochondrial genetic polymorphisms reveals induction of heteroplasmy by pleiotropic disease locus 10398A>G.线粒体遗传多态性建模显示多效性疾病位点 10398A>G 诱导异质性。
Sci Rep. 2023 Jun 27;13(1):10405. doi: 10.1038/s41598-023-37541-y.

本文引用的文献

1
Evolution and functional impact of rare coding variation from deep sequencing of human exomes.人类外显子组深度测序中罕见编码变异的进化和功能影响。
Science. 2012 Jul 6;337(6090):64-9. doi: 10.1126/science.1219240. Epub 2012 May 17.
2
Personal omics profiling reveals dynamic molecular and medical phenotypes.个人组学分析揭示动态的分子和医学表型。
Cell. 2012 Mar 16;148(6):1293-307. doi: 10.1016/j.cell.2012.02.009.
3
A systematic survey of loss-of-function variants in human protein-coding genes.人类蛋白编码基因功能丧失变异的系统调查。
Science. 2012 Feb 17;335(6070):823-8. doi: 10.1126/science.1215040.
4
Genomics and privacy: implications of the new reality of closed data for the field.基因组学与隐私:封闭数据的新现实对该领域的影响。
PLoS Comput Biol. 2011 Dec;7(12):e1002278. doi: 10.1371/journal.pcbi.1002278. Epub 2011 Dec 1.
5
Phased whole-genome genetic risk in a family quartet using a major allele reference sequence.采用主要等位基因参考序列对一个家系四重奏进行分阶段全基因组遗传风险评估。
PLoS Genet. 2011 Sep;7(9):e1002280. doi: 10.1371/journal.pgen.1002280. Epub 2011 Sep 15.
6
Keeping up with genetic discoveries in amyotrophic lateral sclerosis: the ALSoD and ALSGene databases.紧跟肌萎缩侧索硬化症的基因发现:ALSoD和ALS基因数据库。
Amyotroph Lateral Scler. 2011 Jul;12(4):238-49. doi: 10.3109/17482968.2011.584629.
7
A probabilistic disease-gene finder for personal genomes.个人基因组的概率疾病基因查找器。
Genome Res. 2011 Sep;21(9):1529-42. doi: 10.1101/gr.123158.111. Epub 2011 Jun 23.
8
Using VAAST to identify an X-linked disorder resulting in lethality in male infants due to N-terminal acetyltransferase deficiency.利用 VAAST 鉴定一种 X 连锁疾病,该疾病导致男性婴儿因 N 端乙酰转移酶缺乏而致死。
Am J Hum Genet. 2011 Jul 15;89(1):28-43. doi: 10.1016/j.ajhg.2011.05.017. Epub 2011 Jun 23.
9
Somatic coding mutations in human induced pluripotent stem cells.人类诱导多能干细胞中的体细胞编码突变。
Nature. 2011 Mar 3;471(7336):63-7. doi: 10.1038/nature09805.
10
A map of human genome variation from population-scale sequencing.人类基因组变异的图谱来自于基于人群的测序。
Nature. 2010 Oct 28;467(7319):1061-73. doi: 10.1038/nature09534.

一个促进基因组临床应用的公共资源。

A public resource facilitating clinical use of genomes.

机构信息

Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.

出版信息

Proc Natl Acad Sci U S A. 2012 Jul 24;109(30):11920-7. doi: 10.1073/pnas.1201904109. Epub 2012 Jul 13.

DOI:10.1073/pnas.1201904109
PMID:22797899
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3409785/
Abstract

Rapid advances in DNA sequencing promise to enable new diagnostics and individualized therapies. Achieving personalized medicine, however, will require extensive research on highly reidentifiable, integrated datasets of genomic and health information. To assist with this, participants in the Personal Genome Project choose to forgo privacy via our institutional review board- approved "open consent" process. The contribution of public data and samples facilitates both scientific discovery and standardization of methods. We present our findings after enrollment of more than 1,800 participants, including whole-genome sequencing of 10 pilot participant genomes (the PGP-10). We introduce the Genome-Environment-Trait Evidence (GET-Evidence) system. This tool automatically processes genomes and prioritizes both published and novel variants for interpretation. In the process of reviewing the presumed healthy PGP-10 genomes, we find numerous literature references implying serious disease. Although it is sometimes impossible to rule out a late-onset effect, stringent evidence requirements can address the high rate of incidental findings. To that end we develop a peer production system for recording and organizing variant evaluations according to standard evidence guidelines, creating a public forum for reaching consensus on interpretation of clinically relevant variants. Genome analysis becomes a two-step process: using a prioritized list to record variant evaluations, then automatically sorting reviewed variants using these annotations. Genome data, health and trait information, participant samples, and variant interpretations are all shared in the public domain-we invite others to review our results using our participant samples and contribute to our interpretations. We offer our public resource and methods to further personalized medical research.

摘要

DNA 测序的快速发展有望带来新的诊断方法和个体化治疗。然而,要实现个性化医疗,还需要对基因组和健康信息的高度可识别、整合数据集进行广泛研究。为了协助这一目标的实现,参与个人基因组计划的参与者通过我们机构审查委员会批准的“开放同意”程序选择放弃隐私。公共数据和样本的贡献既促进了科学发现,也促进了方法的标准化。在超过 1800 名参与者入组后,我们介绍了研究结果,其中包括 10 名试点参与者基因组的全基因组测序(PGP-10)。我们引入了基因组-环境-特征证据(GET-Evidence)系统。该工具可自动处理基因组,并优先对已发表和新的变体进行解释。在审查假定健康的 PGP-10 基因组的过程中,我们发现了许多文献参考资料,暗示存在严重疾病。虽然有时无法排除迟发性效应,但严格的证据要求可以解决偶然发现的高发生率问题。为此,我们开发了一种同行生产系统,根据标准证据指南记录和组织变体评估,为临床相关变体解释达成共识创建一个公共论坛。基因组分析成为一个两步过程:使用优先级列表记录变体评估,然后使用这些注释自动对已审查的变体进行排序。基因组数据、健康和特征信息、参与者样本以及变体解释均在公共领域共享——我们邀请其他人使用我们的参与者样本审查我们的结果,并为我们的解释做出贡献。我们提供我们的公共资源和方法,以进一步推进个性化医学研究。