ArticleNucleic acids research2021
Flexible comparison of batch correction methods for single-cell RNA-seq using BatchBench.
Article in Nucleic acids research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 3 of them syntheses that pooled it.
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Who cites it
55 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Meta-analysis of genomic characteristics for antiviral influenza defective interfering particle prioritization.NAR genomics and bioinformatics · 2025Pooled it
- Meta-analysis of (single-cell method) benchmarks reveals the need for extensibility and interoperability.Genome biology · 2023Pooled it
- Meta-Analysis of Human Cancer Single-Cell RNA-Seq Datasets Using the IMMUcan Database.Cancer research · 2023Pooled it
- Moderated designs can balance between batch-effect mitigation and cell loss due to hashtag-assisted pooling in single-cell experiments.Genome research · 2026Article
- SC-framework: A robust and FAIR semi-interactive environment for single-cell resolution datasets.iScience · 2026Article
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- Benchmarking the prediction of responding cells to perturbations affecting both gene expression and cellular abundance using scRNA sequencing.Scientific reports · 2026Article
- Integration of large, complex single-cell datasets with Harmony2.bioRxiv : the preprint server for biology · 2026Article
- Article
- Exploring phenotype-related single-cells through attention-enhanced representation learning.Genome medicine · 2026Article
- Development and comparison of evaluation metrics for batch correction reveals performance differences.Bioinformatics advances · 2026Article
- Article
- Single-Cell Multi-Omics in Type 2 Diabetes Mellitus: Revealing Cellular Heterogeneity and Mechanistic Insights.International journal of molecular sciences · 2025Review
- Moderated designs can balance between batch-effect mitigation and cell loss due to hashtag-assisted pooling in single-cell experiments.bioRxiv : the preprint server for biology · 2025Article
- A mesothelial differentiation gateway drives fibrosis.Nature communications · 2025Article
- Triple-effect correction for Cell Painting data with contrastive and domain-adversarial learning.Nature communications · 2025Article
- Defining and benchmarking open problems in single-cell analysis.Nature biotechnology · 2025Article
- Evidence for Transcriptomic Conservation Between the Main Cells of thebioRxiv : the preprint server for biology · 2025Article
- Feature selection methods affect the performance of scRNA-seq data integration and querying.Nature methods · 2025Article
- Human Pancreatic Cancer Single-Cell Atlas Reveals Association of CXCL10+ Fibroblasts and Basal Subtype Tumor Cells.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
As the cost of single-cell RNA-seq experiments has decreased, an increasing number of datasets are now available. Combining newly generated and publicly accessible datasets is challenging due to non-biological signals, commonly known as batch effects. Although there are several computational methods available that can remove batch effects, evaluating which method performs best is not straightforward. Here, we present BatchBench (https://github.com/cellgeni/batchbench), a modular and flexible pipeline for comparing batch correction methods for single-cell RNA-seq data. We apply BatchBench to eight methods, highlighting their methodological differences and assess their performance and computational requirements through a compendium of well-studied datasets. This systematic comparison guides users in the choice of batch correction tool, and the pipeline makes it easy to evaluate other datasets.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.