Abstract
Single-cell RNA-seq has the potential to facilitate isoform quantification as the confounding factor of a mixed population of cells is eliminated. We carried out a benchmark for five popular isoform quantification tools. Performance was generally good when run on simulated data based on SMARTer and SMART-seq2 data, but was poor for simulated Drop-seq data. Importantly, the reduction in performance for single-cell RNA-seq compared with bulk RNA-seq was small. An important biological insight comes from our analysis of real data which showed that genes that express two isoforms in bulk RNA-seq predominantly express one or neither isoform in individual cells.
Copyright
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