Journal
NUCLEIC ACIDS RESEARCH
Volume 49, Issue 7, Pages -Publisher
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkab004
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Funding
- Wellcome Trust
- Polytechnic University of Valencia [Erasmus+]
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With the decreasing cost of single-cell RNA-seq experiments, there is an increasing number of available datasets. However, combining these datasets is challenging due to batch effects. BatchBench is a modular and flexible pipeline designed to compare batch correction methods for single-cell RNA-seq data, helping users choose the most suitable correction tool.
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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