Simulation-based benchmarking of isoform quantification in single-cell RNA-seq.
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Westoby, J., Herrera, M. S., Ferguson-Smith, A., & Hemberg, M. (2018). Simulation-based benchmarking of isoform quantification in single-cell RNA-seq.. Genome biology, 19 (1), 191. https://doi.org/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.
B-Lymphocytes, Cells, Cultured, Animals, Mice, Protein Isoforms, RNA, Gene Expression Profiling, Sequence Analysis, RNA, Computer Simulation, Software, Benchmarking, Single-Cell Analysis, High-Throughput Nucleotide Sequencing
Wellcome Trust (095606/Z/11/Z)
External DOI: https://doi.org/10.1186/s13059-018-1571-5
This record's URL: https://www.repository.cam.ac.uk/handle/1810/286392
Attribution 4.0 International
Licence URL: https://creativecommons.org/licenses/by/4.0/