Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, Basel 4058, Switzerland.
Institute of Microbiology, ETH Zurich, Vladimir-Prelog-Weg 4, Zurich 8093, Switzerland.
Bioinformatics. 2023 Sep 2;39(9). doi: 10.1093/bioinformatics/btad553.
The maturation of systems immunology methodologies requires novel and transparent computational frameworks capable of integrating diverse data modalities in a reproducible manner.
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.
Platypus code used in this manuscript can be found at github.com/alexyermanos/Platypus.
系统免疫学方法的成熟需要新颖且透明的计算框架，这些框架能够以可重复的方式整合不同的数据模式。
在这里，我们展示了用于免疫基因组学数据分析的 ePlatypus 计算免疫学生态系统，重点是适应性免疫受体库和单细胞测序。ePlatypus 是一个开源的基于网络的平台，并提供编程教程和综合数据库，有助于阐明 B 和 T 细胞克隆选择的特征。此外，该生态系统链接了与单细胞免疫受体库以及计算免疫学的其他方面（如预测配体-受体相互作用、结构建模、模拟、机器学习、图论、伪时间、空间转录组学和系统发生学）相关的新的和已建立的生物信息学管道。ePlatypus 生态系统有助于在计算免疫学和免疫基因组学中提取更深入的见解，并促进开放科学。
本文中使用的 Platypus 代码可以在 github.com/alexyermanos/Platypus 上找到。
