scBatch: batch-effect correction of RNA-seq data through sample distance matrix adjustment
scBatch: batch-effect correction of RNA-seq data through sample distance matrix adjustment
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DOI：
10.1093/bioinformatics/btaa097
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发表时间：
2020-05-15
期刊：
影响因子：
5.8
通讯作者：
Yu, Tianwei
中科院分区：
文献类型：
--
作者：
Fei, Teng;Yu, Tianwei
动机：批量效应是深度测序数据分析中的一个常见挑战，可能会导致误导性的结论。现有方法不能令人满意地校正批次效应，尤其是单细胞 RNA 测序 (RNA-seq) 数据。结果：我们提出了 scBatch，一种用于批量和单细胞 RNA-seq 数据批次效应校正的数值算法，重点是改进聚类和基因差异表达分析。 scBatch 不受批次效应生成机制假设的限制。如模拟和实际数据分析所示，scBatch 优于基准批次效应校正方法。
Motivation: Batch effect is a frequent challenge in deep sequencing data analysis that can lead to misleading conclusions. Existing methods do not correct batch effects satisfactorily, especially with single-cell RNA sequencing (RNA-seq) data.Results: We present scBatch, a numerical algorithm for batch-effect correction on bulk and single-cell RNA-seq data with emphasis on improving both clustering and gene differential expression analysis. scBatch is not restricted by assumptions on the mechanism of batch-effect generation. As shown in simulations and real data analyses, scBatch outperforms benchmark batch-effect correction methods.