OmicScope unravels systems-level insights from quantitative proteomics data

Guilherme Reis- de-Oliveira (), Victor Corasolla Carregari, Gabriel Rodrigues dos Reis de Sousa and Daniel Martins- de-Souza ()
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Guilherme Reis- de-Oliveira: University of Campinas (UNICAMP)
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)

Nature Communications, 2024, vol. 15, issue 1, 1-12

Abstract: 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.

Date: 2024
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DOI: 10.1038/s41467-024-50875-z

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