The SpliZ generalizes 'percent spliced in' to reveal regulated splicing at single-cell resolution

被引:15
作者
Olivieri, Julia Eve [1 ,2 ]
Dehghannasiri, Roozbeh [1 ,3 ]
Salzman, Julia [1 ,3 ]
机构
[1] Stanford Univ, Dept Biomed Data Sci, Stanford, CA 94305 USA
[2] Stanford Univ, Inst Computat & Math Engn, Stanford, CA 94305 USA
[3] Stanford Univ, Dept Biochem, Stanford, CA 94305 USA
基金
美国国家科学基金会;
关键词
RNA; ROBUST;
D O I
10.1038/s41592-022-01400-x
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Detecting single-cell-regulated splicing from droplet-based technologies is challenging. Here, we introduce the splicing Z score (SpliZ), an annotation-free statistical method to detect regulated splicing in single-cell RNA sequencing. We applied the SpliZ to human lung cells, discovering hundreds of genes with cell-type-specific splicing patterns including ones with potential implications for basic and translational biology. The Splicing Z Score (SpliZ) provides single-cell-level quantification of alternative splicing with improved statistical power.
引用
收藏
页码:307 / +
页数:19
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