Department of Genetics, University of Cambridge, Downing Street, Cambridge, CB2 3EH, UK.
Departamento de Biología Celular y Molecular, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Av. Libertador Bernardo O'Higgins 340, 8331150, Santiago, Chile.
Genome Biol. 2018 Nov 7;19(1):191. doi: 10.1186/s13059-018-1571-5.
Single-cell RNA-seq has the potential to facilitate isoform quantification as the confounding factor of a mixed population of cells is eliminated. However, best practice for using existing quantification methods has not been established. We carry out a benchmark for five popular isoform quantification tools. Performance is generally good for simulated data based on SMARTer and SMART-seq2 data. The reduction in performance compared with bulk RNA-seq is small. An important biological insight comes from our analysis of real data which shows that genes that express two isoforms in bulk RNA-seq predominantly express one or neither isoform in individual cells.
单细胞 RNA 测序有可能促进异构体定量,因为它消除了细胞混合群体的混杂因素。然而,尚未建立使用现有定量方法的最佳实践。我们对五个流行的异构体定量工具进行了基准测试。基于 SMARTer 和 SMART-seq2 数据的模拟数据的性能通常很好。与批量 RNA-seq 相比,性能的降低很小。一个重要的生物学见解来自于我们对真实数据的分析,该分析表明,在批量 RNA-seq 中表达两种异构体的基因在单个细胞中主要表达一种或两种异构体都不表达。