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本文引用的文献

1
TRIP - T cell receptor/immunoglobulin profiler.TRIP - T 细胞受体/免疫球蛋白分析。
BMC Bioinformatics. 2020 Sep 29;21(1):422. doi: 10.1186/s12859-020-03669-1.
2
T-Cell Dynamics in Chronic Lymphocytic Leukemia under Different Treatment Modalities.不同治疗方式下慢性淋巴细胞白血病中的 T 细胞动力学。
Clin Cancer Res. 2020 Sep 15;26(18):4958-4969. doi: 10.1158/1078-0432.CCR-19-3827. Epub 2020 Jul 2.
3
Celebrating 20 Years of IGHV Mutation Analysis in CLL.庆祝慢性淋巴细胞白血病IGHV突变分析20周年。
Hemasphere. 2020 Jan 22;4(1):e334. doi: 10.1097/HS9.0000000000000334. eCollection 2020 Feb.
4
Next-generation sequencing in chronic lymphocytic leukemia: recent findings and new horizons.慢性淋巴细胞白血病中的下一代测序:最新发现与新视野
Oncotarget. 2017 Jul 24;8(41):71234-71248. doi: 10.18632/oncotarget.19525. eCollection 2017 Sep 19.
5
ARResT/Interrogate: an interactive immunoprofiler for IG/TR NGS data.ARResT/Interrogate:用于 IG/TR NGS 数据的交互式免疫分析工具。
Bioinformatics. 2017 Feb 1;33(3):435-437. doi: 10.1093/bioinformatics/btw634.
6
Vidjil: A Web Platform for Analysis of High-Throughput Repertoire Sequencing.Vidjil:一个用于分析高通量序列库测序的网络平台。
PLoS One. 2016 Nov 11;11(11):e0166126. doi: 10.1371/journal.pone.0166126. eCollection 2016.
7
IMGT/StatClonotype for Pairwise Evaluation and Visualization of NGS IG and TR IMGT Clonotype (AA) Diversity or Expression from IMGT/HighV-QUEST.IMGT/StatClonotype用于对来自IMGT/HighV-QUEST的NGS免疫球蛋白(IG)和T细胞受体(TR)IMGT克隆型(氨基酸序列)多样性或表达进行成对评估和可视化。
Front Immunol. 2016 Sep 9;7:339. doi: 10.3389/fimmu.2016.00339. eCollection 2016.
8
A complementary role of multiparameter flow cytometry and high-throughput sequencing for minimal residual disease detection in chronic lymphocytic leukemia: an European Research Initiative on CLL study.多参数流式细胞术和高通量测序在慢性淋巴细胞白血病微小残留病检测中的互补作用:一项欧洲慢性淋巴细胞白血病研究倡议。
Leukemia. 2016 Apr;30(4):929-36. doi: 10.1038/leu.2015.313. Epub 2015 Dec 7.
9
IMGT/HighV-QUEST Statistical Significance of IMGT Clonotype (AA) Diversity per Gene for Standardized Comparisons of Next Generation Sequencing Immunoprofiles of Immunoglobulins and T Cell Receptors.IMGT/HighV-QUEST:用于免疫球蛋白和T细胞受体下一代测序免疫谱标准化比较的每个基因IMGT克隆型(氨基酸)多样性的统计显著性
PLoS One. 2015 Nov 5;10(11):e0142353. doi: 10.1371/journal.pone.0142353. eCollection 2015.
10
IMSEQ--a fast and error aware approach to immunogenetic sequence analysis.IMSEQ——一种快速且具备错误感知能力的免疫遗传序列分析方法。
Bioinformatics. 2015 Sep 15;31(18):2963-71. doi: 10.1093/bioinformatics/btv309. Epub 2015 May 18.

专为 BcR IG/TR repertoire 数据分析而设计的免疫信息学。

Purpose-Built Immunoinformatics for BcR IG/TR Repertoire Data Analysis.

机构信息

Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece.

Department of Molecular Biology and Genetics (MBG), Democritus University of Thrace, Alexandroupolis, Greece.

出版信息

Methods Mol Biol. 2022;2453:585-603. doi: 10.1007/978-1-0716-2115-8_27.

DOI:10.1007/978-1-0716-2115-8_27
PMID:35622343
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9761556/
Abstract

The study of antigen receptor gene repertoires using next-generation sequencing (NGS) technologies has disclosed an unprecedented depth of complexity, requiring novel computational and analytical solutions. Several bioinformatics workflows have been developed to this end, including the T-cell receptor/immunoglobulin profiler (TRIP), a web application implemented in R shiny, specifically designed for the purposes of comprehensive repertoire analysis, which is the focus of this chapter. TRIP has the potential to perform robust immunoprofiling analysis through the extraction and processing of the IMGT/HighV-Quest output, via a series of functions, ensuring the analysis of high-quality, biologically relevant data through a multilevel process of data filtering. Subsequently, it provides in-depth analysis of antigen receptor gene rearrangements, including (a) clonality assessment; (b) extraction of variable (V), diversity (D), and joining (J) gene repertoires; (c) CDR3 characterization at both the nucleotide and amino acid level; and (d) somatic hypermutation analysis, in the case of immunoglobulin gene rearrangements. Relevant to mention, TRIP enables a high level of customization through the integration of various options in key aspects of the analysis, such as clonotype definition and computation, hence allowing for flexibility without compromising on accuracy.

摘要

使用下一代测序 (NGS) 技术研究抗原受体基因库,揭示了前所未有的复杂性,这需要新的计算和分析解决方案。为此已经开发了几种生物信息学工作流程,包括 T 细胞受体/免疫球蛋白分析器 (TRIP),这是一个在 R shiny 中实现的 Web 应用程序,专门设计用于全面的库分析,这是本章的重点。TRIP 具有通过提取和处理 IMGT/HighV-Quest 输出进行强大免疫分析的潜力,通过一系列功能确保通过多层次的数据过滤过程分析高质量、有生物学意义的数据。随后,它提供了对抗原受体基因重排的深入分析,包括 (a) 克隆性评估;(b) 提取可变 (V)、多样性 (D) 和连接 (J) 基因库;(c) 在核苷酸和氨基酸水平上对 CDR3 进行特征描述;以及 (d) 在免疫球蛋白基因重排的情况下进行体细胞超突变分析。值得一提的是,TRIP 通过在分析的关键方面集成各种选项(例如克隆型定义和计算),实现了高水平的定制化,从而在不影响准确性的情况下具有灵活性。