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

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 quantificati...

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Detalles Bibliográficos
Autores principales: Westoby, Jennifer, Herrera, Marcela Sjöberg, Ferguson-Smith, Anne C., Hemberg, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6223048/
https://www.ncbi.nlm.nih.gov/pubmed/30404663
http://dx.doi.org/10.1186/s13059-018-1571-5
Descripción
Sumario: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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-018-1571-5) contains supplementary material, which is available to authorized users.