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OmicScope unravels systems-level insights from quantitative proteomics data

Author

Listed:
  • Guilherme Reis-de-Oliveira

    (University of Campinas (UNICAMP)
    Boldrini Children’s Hospital)

  • Victor Corasolla Carregari

    (University of Campinas (UNICAMP))

  • Gabriel Rodrigues dos Reis de Sousa

    (University of Campinas (UNICAMP))

  • Daniel Martins-de-Souza

    (University of Campinas (UNICAMP)
    University of Campinas (UNICAMP)
    Instituto Nacional de Biomarcadores Em Neuropsiquiatria (INBION) Conselho Nacional de Desenvolvimento Científico E Tecnológico
    University of Campinas)

Abstract

Shotgun proteomics analysis presents multifaceted challenges, demanding diverse tool integration for insights. Addressing this complexity, OmicScope emerges as an innovative solution for quantitative proteomics data analysis. Engineered to handle various data formats, it performs data pre-processing – including joining replicates, normalization, data imputation – and conducts differential proteomics analysis for both static and longitudinal experimental designs. Empowered by Enrichr with over 224 databases, OmicScope performs Over Representation Analysis (ORA) and Gene Set Enrichment Analysis (GSEA). Additionally, its Nebula module facilitates meta-analysis from independent datasets, providing a systems biology approach for enriched insights. Complete with a data visualization toolkit and accessible as Python package and a web application, OmicScope democratizes proteomics analysis, offering an efficient and high-quality pipeline for researchers.

Suggested Citation

  • Guilherme Reis-de-Oliveira & Victor Corasolla Carregari & Gabriel Rodrigues dos Reis de Sousa & Daniel Martins-de-Souza, 2024. "OmicScope unravels systems-level insights from quantitative proteomics data," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-50875-z
    DOI: 10.1038/s41467-024-50875-z
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