ePlatypus: an ecosystem for computational analysis of immunogenomics data

Author:

Cotet Tudor-Stefan1,Agrafiotis Andreas12ORCID,Kreiner Victor1,Kuhn Raphael1,Shlesinger Danielle1,Manero-Carranza Marcos1ORCID,Khodaverdi Keywan1,Kladis Evgenios1,Desideri Perea Aurora3,Maassen-Veeters Dylan3,Glänzer Wiona1,Massery Solène1,Guerci Lorenzo1,Hong Kai-Lin1,Han Jiami1,Stiklioraitis Kostas1,D’Arcy Vittoria Martinolli1,Dizerens Raphael1,Kilchenmann Samuel1,Stalder Lucas1,Nissen Leon1,Vogelsanger Basil1,Anzböck Stine1,Laslo Daria1,Bakker Sophie3,Kondorosy Melinda1,Venerito Marco1,Sanz García Alejandro1,Feller Isabelle1,Oxenius Annette2,Reddy Sai T1,Yermanos Alexander1234ORCID

Affiliation:

1. Department of Biosystems Science and Engineering, ETH Zurich , Mattenstrasse 26 , Basel 4058, Switzerland

2. Institute of Microbiology, ETH Zurich , Vladimir-Prelog-Weg 4 , Zurich 8093, Switzerland

3. Center for Translational Immunology, University Medical Center Utrecht , Lundlaan 6 , Utrecht 3584 EA, The Netherlands

4. Department of Pathology and Immunology, University of Geneva , 24 rue du Général-Dufour , Geneva 1211, Switzerland

Abstract

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.

Funder

ETH Zurich Research

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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