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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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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 |
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author | Westoby, Jennifer Herrera, Marcela Sjöberg Ferguson-Smith, Anne C. Hemberg, Martin |
author_facet | Westoby, Jennifer Herrera, Marcela Sjöberg Ferguson-Smith, Anne C. Hemberg, Martin |
author_sort | Westoby, Jennifer |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6223048 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-62230482018-11-19 Simulation-based benchmarking of isoform quantification in single-cell RNA-seq Westoby, Jennifer Herrera, Marcela Sjöberg Ferguson-Smith, Anne C. Hemberg, Martin Genome Biol Method 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. BioMed Central 2018-11-07 /pmc/articles/PMC6223048/ /pubmed/30404663 http://dx.doi.org/10.1186/s13059-018-1571-5 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Method Westoby, Jennifer Herrera, Marcela Sjöberg Ferguson-Smith, Anne C. Hemberg, Martin Simulation-based benchmarking of isoform quantification in single-cell RNA-seq |
title | Simulation-based benchmarking of isoform quantification in single-cell RNA-seq |
title_full | Simulation-based benchmarking of isoform quantification in single-cell RNA-seq |
title_fullStr | Simulation-based benchmarking of isoform quantification in single-cell RNA-seq |
title_full_unstemmed | Simulation-based benchmarking of isoform quantification in single-cell RNA-seq |
title_short | Simulation-based benchmarking of isoform quantification in single-cell RNA-seq |
title_sort | simulation-based benchmarking of isoform quantification in single-cell rna-seq |
topic | Method |
url | 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 |
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