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

Published version
Peer-reviewed

Type

Article

Change log

Authors

Westoby, Jennifer 
Herrera, Marcela Sjöberg 
Ferguson-Smith, Anne C 

Abstract

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.

Description

Keywords

Benchmark, Bulk RNA-seq, Isoform quantification, Single cell, scRNA-seq, Animals, B-Lymphocytes, Benchmarking, Cells, Cultured, Computer Simulation, Gene Expression Profiling, High-Throughput Nucleotide Sequencing, Mice, Protein Isoforms, RNA, Sequence Analysis, RNA, Single-Cell Analysis, Software

Journal Title

Genome Biol

Conference Name

Journal ISSN

1474-7596
1474-760X

Volume Title

19

Publisher

Springer Science and Business Media LLC
Sponsorship
Wellcome Trust (095606/Z/11/Z)
Biotechnology and Biological Sciences Research Council (1804962)
Biotechnology and Biological Sciences Research Council (BB/M011194/1)
Medical Research Council (MR/R009791/1)