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EasyMultiProfiler: an efficient multi-omics data integration and analysis workflow for microbiome research
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AI
DOI：10.1007/s11427-025-3035-0.png)
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Abstract
En 中文
Host-microbiome interactions are crucial for physiological homeostasis and disease progression. While traditional microbiome research provided foundational insights, multi-omics approaches enable a more comprehensive and systems-level understanding. However, integrating multi-omics data presents significant methodological challenges, including inconsistent sample coverage, heterogeneous data formats, and complex analytical workflows, which collectively impair reproducibility and reliability. To address these critical challenges, we developed the EasyMultiProfiler (EMP), a streamlined and efficient analytical workflow. EMP utilizes SummarizedExperiment and MultiAssayExperiment classes to establish a unified multi-omics data storage and analysis framework. Its architecture comprises five interconnected functional modules: data extraction, preparation, support, analysis, and visualization, integrated into a user-friendly and natural language-style workflow. This design offers an efficient and standardized solution, directly resolving data integration issues, workflow standardization, and result reproducibility. EMP provides researchers and clinicians with a robust and flexible platform to systematically extract biologically relevant insights from complex multi-omics datasets, overcoming key barriers in contemporary microbiome research.
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