Simulation-based benchmarking of isoform quantification in single-cell RNA-seq

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.

Keywords: Benchmark; Bulk RNA-seq; Isoform quantification; Single cell; scRNA-seq.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • B-Lymphocytes / metabolism*
  • Benchmarking
  • Cells, Cultured
  • Computer Simulation*
  • Gene Expression Profiling
  • High-Throughput Nucleotide Sequencing / methods*
  • Mice
  • Protein Isoforms
  • RNA / analysis*
  • RNA / genetics
  • Sequence Analysis, RNA
  • Single-Cell Analysis / methods*
  • Software*


  • Protein Isoforms
  • RNA