article Open AccessTop 1% cited
A benchmark of batch-effect correction methods for single-cell RNA sequencing data
Genome biology · 2020 · Vol. 21(1) · pp. 12–12
Hoa Thi Tran✉(Agency for Science, Technology and Research)Kok Siong Ang(Agency for Science, Technology and Research)Marion Chevrier(Agency for Science, Technology and Research)Xiaomeng Zhang(Agency for Science, Technology and Research)Nicole Yee Shin Lee(Agency for Science, Technology and Research)Michelle Goh(Agency for Science, Technology and Research)Jinmiao Chen(Agency for Science, Technology and Research)
Abstract
Based on our results, Harmony, LIGER, and Seurat 3 are the recommended methods for batch integration. Due to its significantly shorter runtime, Harmony is recommended as the first method to try, with the other methods as viable alternatives.
Single-cell and spatial transcriptomicsExtracellular vesicles in diseaseMicroRNA in disease regulationBenchmark (surveying)BenchmarkingComputer scienceBatch processingData miningData integration
MeSH terms
Big DataRNA-SeqAlgorithmsAnimalsHumansBenchmarkingMiceSingle-Cell Analysis
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A benchmark of batch-effect correction methods for single-cell RNA sequencing data
Genome biology · 2020 · 1,177 citations
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