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Next-generation Sequencing

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....

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相关实验视频

Updated: Jun 29, 2025

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

通过本地下一代测序训练数据改进HLA类型赋值准确性和eplet识别,提高当地下一代测序训练数据的准确性.

Romain Lhotte^1,2,3, Véronique Letort², Cédric Usureau¹

¹Immunology and Histocompatibility Laboratory, Saint-Louis Hospital, Paris, France.

|April 8, 2024

概括

哈普洛SFHI从低分辨率数据中准确地归因高分辨率的人类白细胞抗原 (HLA) 类型,改进了捐赠者-接受者兼容性评估. 这种方法通过确定测序的最佳候选人来提高HLA类型的成本效益.

关键词:

哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈哈子子子子他的兼容性与不兼容性.归算是指指责一个人.下一代测序 (NGS) 是指下一代的测序.

更多相关视频

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

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Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing

Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing

Published on: March 15, 2019

相关实验视频

Last Updated: Jun 29, 2025

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

Detection of Rare Mutations in CtDNA Using Next Generation Sequencing

Published on: August 24, 2017

Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing

Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing

Published on: March 15, 2019

科学领域:

免疫遗传学免疫遗传学
计算生物学计算生物学
移植科学移植科学

背景情况:

准确的人类白细胞抗原 (HLA) 排型对于捐赠者与接受者的兼容性至关重要,特别是在片水平上.
第二个场的HLA类型,对于片级评估所需的,并不总是可用,并且需要从更低分辨率的数据中进行归算.
现有的HLA归算的计算工具通常依赖于模两可的数据,限制了预测的准确性.

研究的目的:

开发和验证一种新的计算工具,HaploSFHI,用于从低或中等分辨率数据中归纳第二场HLA类型.
将HaploSFHI的性能与使用广泛数据集的现有归算工具进行比较.
为优化HLA类型化策略提供指导,以提高成本效益和改进不兼容性评估.

主要方法:

收集了来自17个法国实验室的61,393名个体的下一代测序 (NGS) 类型数据,用于多个HLA位点.
开发HaploSFHI,一种修改的代最大概率算法,用于归因高分辨率的HLA类型.
通过使用法国和欧洲独立的测试集,对HaploStats,HLA-EMMA和HLA-Upgrade进行了验证HaploSFHI性能.

主要成果:

与参考工具相比,HaploSFHI在所有测试位点中赋予第二场HLA类型的准确性更高.
HaploSFHI是唯一能够赋值DQA1的工具,它与HaploStats一起提供了DRB3/4/5的赋值.
分析发现了常见的归算错误和单元型变异性,为选择个人进行确认测序的策略提供了信息.

结论:

哈普洛SFHI显著提高了HLA归算的准确性,特别是在像DQA1和DRB3/4/5.5这样的位置上.
该工具的性能归功于使用本地,不含糊的数据,为估计高分辨率HLA类型提供了可靠的方法.
哈普洛SFHI通过指导测序对不兼容性评估最有利的个体的选择,促进了成本效益高的HLA类型.