计算机科学
算法
数据挖掘
比例(比率)
量子力学
物理
作者
Jiaqi Li,Chengxuan Yu,Lifeng Ma,Jingjing Wang,Guoji Guo
标识
DOI:10.1186/s13619-020-00041-9
摘要
Abstract With the development of single-cell RNA sequencing (scRNA-seq) technology, analysts need to integrate hundreds of thousands of cells with multiple experimental batches. It is becoming increasingly difficult for users to select the best integration methods to remove batch effects. Here, we compared the advantages and limitations of four commonly used Scanpy-based batch-correction methods using two representative and large-scale scRNA-seq datasets. We quantitatively evaluated batch-correction performance and efficiency. Furthermore, we discussed the performance differences among the evaluated methods at the algorithm level.
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