Quantifying batch effects for individual genes in single-cell data
数学学科创建110周年系列报告
报告题目(Title)：Quantifying batch effects for individual genes in single-cell data
报告人(Speaker)： 靳水林 (哈尔滨工业大学)
地点(Place)：后主楼1220
时间(Time)：2025年5月21日 周三 10:00-11:00
邀请人(Inviter)：段玉萍
报告摘要
Batch effects have been a long-standing problem in sequencing data analysis, significantly impeding the comparison of multiple experiment batches. Existing methods for batch effect removal and quantification emphasize cell alignment across batches, overlooking gene-level batch effects. Here, we introduce group technical effects (GTE), a quantitative metric to assess gene-level batch effects. Using GTE, we show the unbalanced gene-level batch effects in single-cell data. A subset of highly batch-sensitive genes (HBGs) is the main contributor to batch effects and varies across datasets, while non-highly batch-sensitive genes (non-HBGs) exhibit minimal batch effects. As few as three HBGs are sufficient to introduce strong batch effects to the data. Furthermore, biologically similar cell types undergo similar batch effects, informing the development of data integration strategies. The GTE method is versatile and applicable to various single-cell omics data types.
