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A benchmark of batch-effect correction methods for single-cell RNA sequencing data

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Large-scale single-cell transcriptomic datasets generated using different technologies contain batchspecific systematic variations that present a challenge to batch-effect removal and data integration. With continued growth expected in scRNA-seq data, achieving effective batch integration with available computational resources is crucial. |

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