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适应性免疫受体测序数据分析可重复性分析指南。

Guidelines for reproducible analysis of adaptive immune receptor repertoire sequencing data.

机构信息

Faculty of Engineering, Bar Ilan University, 5290002 Ramat Gan, Israel.

Bar Ilan institute of nanotechnology and advanced materials, Bar Ilan university, 5290002 Ramat Gan, Israel.

出版信息

Brief Bioinform. 2024 Mar 27;25(3). doi: 10.1093/bib/bbae221.

Abstract

Enhancing the reproducibility and comprehension of adaptive immune receptor repertoire sequencing (AIRR-seq) data analysis is critical for scientific progress. This study presents guidelines for reproducible AIRR-seq data analysis, and a collection of ready-to-use pipelines with comprehensive documentation. To this end, ten common pipelines were implemented using ViaFoundry, a user-friendly interface for pipeline management and automation. This is accompanied by versioned containers, documentation and archiving capabilities. The automation of pre-processing analysis steps and the ability to modify pipeline parameters according to specific research needs are emphasized. AIRR-seq data analysis is highly sensitive to varying parameters and setups; using the guidelines presented here, the ability to reproduce previously published results is demonstrated. This work promotes transparency, reproducibility, and collaboration in AIRR-seq data analysis, serving as a model for handling and documenting bioinformatics pipelines in other research domains.

摘要

增强适应性免疫受体库测序(AIRR-seq)数据分析的可重复性和可理解性对于科学进步至关重要。本研究提出了可重复的 AIRR-seq 数据分析指南,并提供了一组带有全面文档的即用型管道。为此,使用 ViaFoundry 实现了十个常见的管道,这是一个用于管道管理和自动化的用户友好界面。此外,还提供了版本化容器、文档和归档功能。强调了预处理分析步骤的自动化以及根据特定研究需求修改管道参数的能力。AIRR-seq 数据分析对不同的参数和设置非常敏感;使用这里提出的指南,可以重现以前发表的结果。这项工作促进了 AIRR-seq 数据分析的透明度、可重复性和协作,为处理和记录其他研究领域的生物信息学管道提供了模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/47b6/11097599/ea79241fc1b6/bbae221f1.jpg

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