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OmicScope 从定量蛋白质组学数据中揭示系统水平的见解。

OmicScope unravels systems-level insights from quantitative proteomics data.

机构信息

Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, SP, Brazil.

Research Center, Boldrini Children's Hospital, Campinas, SP, Brazil.

出版信息

Nat Commun. 2024 Aug 2;15(1):6510. doi: 10.1038/s41467-024-50875-z.

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.

摘要

shotgun 蛋白质组学分析提出了多方面的挑战,需要多种工具的集成来获得深入的见解。为了解决这一复杂性,OmicScope 作为一种创新的定量蛋白质组学数据分析解决方案应运而生。它旨在处理各种数据格式,执行数据预处理——包括合并重复项、归一化、数据插补——并对静态和纵向实验设计进行差异蛋白质组学分析。通过与 224 个数据库的 Enrichr 相结合,OmicScope 执行了 Over Representation Analysis (ORA) 和 Gene Set Enrichment Analysis (GSEA)。此外,它的 Nebula 模块还可以从独立数据集进行元分析,为丰富的见解提供系统生物学方法。OmicScope 配备了数据可视化工具包,可作为 Python 包和 Web 应用程序使用,使蛋白质组学分析民主化,为研究人员提供了高效、高质量的分析流程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb99/11297029/e2eccf219a6d/41467_2024_50875_Fig1_HTML.jpg

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