ePlatypus: an ecosystem for computational analysis of immunogenomics data.

IF 4.4 3区生物学 Q1 BIOCHEMICAL RESEARCH METHODS Bioinformatics Pub Date : 2023-09-02 DOI:10.1093/bioinformatics/btad553

Tudor-Stefan Cotet, Andreas Agrafiotis, Victor Kreiner, Raphael Kuhn, Danielle Shlesinger, Marcos Manero-Carranza, Keywan Khodaverdi, Evgenios Kladis, Aurora Desideri Perea, Dylan Maassen-Veeters, Wiona Glänzer, Solène Massery, Lorenzo Guerci, Kai-Lin Hong, Jiami Han, Kostas Stiklioraitis, Vittoria Martinolli D'Arcy, Raphael Dizerens, Samuel Kilchenmann, Lucas Stalder, Leon Nissen, Basil Vogelsanger, Stine Anzböck, Daria Laslo, Sophie Bakker, Melinda Kondorosy, Marco Venerito, Alejandro Sanz García, Isabelle Feller, Annette Oxenius, Sai T Reddy, Alexander Yermanos

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Abstract

Motivation: The maturation of systems immunology methodologies requires novel and transparent computational frameworks capable of integrating diverse data modalities in a reproducible manner.

Results: Here, we present the ePlatypus computational immunology ecosystem for immunogenomics data analysis, with a focus on adaptive immune repertoires and single-cell sequencing. ePlatypus is an open-source web-based platform and provides programming tutorials and an integrative database that helps elucidate signatures of B and T cell clonal selection. Furthermore, the ecosystem links novel and established bioinformatics pipelines relevant for single-cell immune repertoires and other aspects of computational immunology such as predicting ligand-receptor interactions, structural modeling, simulations, machine learning, graph theory, pseudotime, spatial transcriptomics, and phylogenetics. The ePlatypus ecosystem helps extract deeper insight in computational immunology and immunogenomics and promote open science.

Availability and implementation: Platypus code used in this manuscript can be found at github.com/alexyermanos/Platypus.

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ePlatypus：用于免疫基因组学数据计算分析的生态系统。

动机：系统免疫学方法的成熟需要新颖透明的计算框架，能够以可复制的方式集成各种数据模式。结果：在这里，我们介绍了用于免疫基因组学数据分析的ePlatypus计算免疫学生态系统，重点是适应性免疫库和单细胞测序。ePlatypus是一个开源的基于网络的平台，提供编程教程和综合数据库，帮助阐明B细胞和T细胞克隆选择的特征。此外，该生态系统连接了与单细胞免疫库和计算免疫学的其他方面相关的新的和已建立的生物信息学管道，如预测配体-受体相互作用、结构建模、模拟、机器学习、图论、假时间、空间转录组学和系统发育学。ePlatypus生态系统有助于深入了解计算免疫学和免疫基因组学，并促进开放科学。可用性和实现：本文中使用的Platypus代码可以在github.com/alexyermanos/Platypus上找到。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Bioinformatics 生物-生化研究方法

CiteScore

11.20

自引率

5.20%

发文量

753

审稿时长

2.1 months

期刊介绍： The leading journal in its field, Bioinformatics publishes the highest quality scientific papers and review articles of interest to academic and industrial researchers. Its main focus is on new developments in genome bioinformatics and computational biology. Two distinct sections within the journal - Discovery Notes and Application Notes- focus on shorter papers; the former reporting biologically interesting discoveries using computational methods, the latter exploring the applications used for experiments.