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cKBET:assessing goodness of batch effect correction for single-cell RNA-seq
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作者 Yameng ZHAO Yin GUO Limin LI 《Frontiers of Computer Science》 SCIE EI CSCD 2024年第1期215-228,共14页
Single-cell RNA sequencing reveals the gene structure and gene expression status of a single cell,which can reflect the heterogeneity between cells.However,batch effects caused by non-biological factors may hinder dat... Single-cell RNA sequencing reveals the gene structure and gene expression status of a single cell,which can reflect the heterogeneity between cells.However,batch effects caused by non-biological factors may hinder data integration and downstream analysis.Although the batch effect can be evaluated by visualizing the data,which actually is subjective and inaccurate.In this work,we propose a quantitative method cKBET,which considers the batch and cell type information simultaneously.The cKBET method accesses batch effects by comparing the global and local fraction of cells of different batches in different cell types.We verify the performance of our cKBET method on simulated and real biological data sets.The experimental results show that our cKBET method is superior to existing methods in most cases.In general,our cKBET method can detect batch effect with either balanced or unbalanced cell types,and thus evaluate batch correction methods. 展开更多
关键词 single-cell RNA-seq dataset b batch effect assessment cKbET method
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