摘要
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.
基金
This work was supported by grants from the National Key Program on Stem Cell and Translational Research(2018YFA0107804,2018YFA0107801 and 2018YFA0800503)
the National Natural Science Foundation of China(91842301,31722027,81770188,31701290 and 31871473)
the Zhejiang Provincial Natural Science Foundation of China(R17H080001)
the Fundamental Research Funds for the Central Universities(G.G.).
