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BatchServer: A Web Server for Batch Effect Evaluation, Visualization, and Correction
Tiansheng Zhu1,2,3,4, Rui Sun2,3,4, Fangfei Zhang2,3,4
1Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, 200438 Shanghai, China.
Journal of Proteome Research
|December 18, 2020
Summary
BatchServer is a new R/Shiny web platform that helps researchers evaluate and correct batch effects in omics data. It uses autoComBat, PVCA, and UMAP for improved data analysis and reliability.
Area of Science:
- Bioinformatics
- Computational Biology
- Data Science
Background:
- Batch effects are common in omics data, introducing unwanted variations that can bias analysis.
- Accurate evaluation and correction of batch effects are crucial for reliable omics data interpretation.
Purpose of the Study:
- To introduce BatchServer, a user-friendly R/Shiny web platform for interactive batch effect analysis.
- To provide a tool that facilitates both the evaluation and correction of batch effects in omics datasets.
Main Methods:
- BatchServer integrates Principal Variance Component Analysis (PVCA) and Uniform Manifold Approximation and Projection (UMAP) for batch effect evaluation and visualization.
- It features autoComBat, a modified version of the widely used ComBat tool, for batch effect correction.
Main Results:
- The platform demonstrates effective application in analyzing multiple proteomics and transcriptomic datasets.
- BatchServer provides an interactive graphical interface for streamlined batch effect assessment.
Conclusions:
- BatchServer offers a valuable, open-source solution for addressing batch effects in omics data analysis.
- The tool enhances the reliability and accuracy of omics data interpretation through effective batch effect management.
