BatchServer: a web server for batch effect evaluation, visualization and correction
Tiansheng ZhuiD, Rui SuniD, Fangfei ZhangiD, Guo‐Bo CheniD, Xiao YiiD, Guan RuaniD, Chunhui YuaniD, Shuigeng ZhouiD, Tiannan GuoiD
Abstract
Batch effects are unwanted data variations that may obscure biological signals, leading to bias or errors in subsequent data analyses. Effective evaluation and elimination of batch effects are necessary for omics data analysis. In order to facilitate the evaluation and correction of batch effects, here we present BatchSever, an open-source R/Shiny based user-friendly interactive graphical web platform for batch effects analysis. In BatchServer we introduced autoComBat, a modified version of ComBat, which is the most widely adopted tool for batch effect correction. BatchServer uses PVCA (Principal Variance Component Analysis) and UMAP (Manifold Approximation and Projection) for evaluation and visualizion of batch effects. We demonstate its application in multiple proteomics and transcriptomic data sets. BatchServer is provided at https://lifeinfo.shinyapps.io/batchserver/ as a web server. The source codes are freely available at https://github.com/guomics-lab/batch_server.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 24
- FWCI
- 0.81
- Field percentile
- top 31%
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Reproducible Tools and Enhanced Computational Workflows for Batch Effect Evaluation of High-Throughput Data Using BatchQC
Jessica McClintock, Jiwei Zhang, … Alzheimer’s Disease Neuroimaging Initiative·bioRxiv·Feb 13, 2026
- reComBat: Batch effect removal in large-scale, multi-source omics data integration
Michael F. Adamer, Sarah C. Brüningk, … Karsten Michael Borgwardt·Bioinformatics AdvancesPeer-reviewed·Jan 1, 2022
- pyComBat, a Python tool for batch effects correction in high-throughput molecular data using empirical Bayes methods
Abdelkader Behdenna, Maximilien Colange, … Akpéli V. Nordor·BMC BioinformaticsPeer-reviewed·Dec 6, 2023
- BatchEval Pipeline: Batch Effect Evaluation Workflow for Multiple Datasets Joint Analysis
Chao Zhang, Qiang Kang, … Xun Xu·GigabytePeer-reviewed·Feb 19, 2024
- Assessment of batch-correction methods for scRNA-seq data with a new test metric
Maren Büttner, Zhichao Miao, … Fabian Joachim Theis·Nature MethodsPeer-reviewed·Dec 10, 2018
- NPmatch: Latent Batch Effects Correction of Omics data by Nearest-Pair Matching
Antonino Zito, Axel Martinelli, … Ivo Kwee·bioRxiv·Apr 29, 2024