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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The ePlatypus ecosystem helps extract deeper insight in computational immunology and immunogenomics and promote open science.</p><p><strong>Availability and implementation: </strong>Platypus code used in this manuscript can be found at github.com/alexyermanos/Platypus.</p>","PeriodicalId":8903,"journal":{"name":"Bioinformatics","volume":" ","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2023-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10518073/pdf/","citationCount":"0","resultStr":"{\"title\":\"ePlatypus: an ecosystem for computational analysis of immunogenomics data.\",\"authors\":\"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\",\"doi\":\"10.1093/bioinformatics/btad553\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Motivation: </strong>The maturation of systems immunology methodologies requires novel and transparent computational frameworks capable of integrating diverse data modalities in a reproducible manner.</p><p><strong>Results: </strong>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. 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ePlatypus: an ecosystem for computational analysis of immunogenomics data.
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.
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.
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