About this resource

    Type of resources
    Reading
    Education level(s)
    College / Upper Division (Undergraduates), Graduate / Professional
    Primary user(s)
    Student, Teacher, Researcher
    Subject area(s)
    Life Science
    Language(s)
    English
    Cluster
    Transparency and Reproducibility in Computation and Analysis
    Last updated
    11 September 2023

    ePlatypus: an ecosystem for computational analysis of immunogenomics data

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    Level College / Upper Division (Undergraduates), Graduate / Professional · For Student, Teacher, Researcher · Language English

    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.

    Keywords Systems Immunology · Bioinformatics · Computational Immunology · Ligand-receptor Interactions · Structural Modeling · Simulations · Machine Learning · Graph Theory · Pseudotime · Spatial Transcriptomics · Phylogenetics