bioRxivImmunologyPreprint
ePlatypus: an ecosystem for computational analysis of immunogenomics data
V. Kreiner, A. Agrafiotis, T.-S. Cotet, R. Kuhn, D. Shlesinger, M. Manero-Carranza, K. Khodaverdi, S. Masserey, L. Guerci, K.-L. Hong, J. Han, K. Stiklioraitis, V. Martinolli, R. Dizerens, S. Kilchenmann, L. Stalder, L. Nissen, B. Vogelsanger, S. Anzböck, D. Laslo, M. Kondorosy, M. Venerito, A. S. Garcia, I. Feller, A. Oxenius, , A. Yermanos
Abstract
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 a web-based platform and provides programming tutorials and an integrative database that elucidates selection patterns of adaptive immunity. 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. Accessibilityhttps://alexyermanos.github.io/Platypus/index.html
- assay: bulk RNA-seq
- assay: spatial transcriptomics
- assay: proteomics
- research focus: cell type annotation
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: deep learning
- approach: statistical model
- approach: simulation
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