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Comparison of methods to detect differentially expressed genes between single-cell populations
We compared five statistical methods to detect differentially expressed genes between two distinct single-cell populations. Currently, it remains unclear whether differential expression methods developed originally for conventional bulk RNA-seq data can also be applied to single-cell RNA-seq data an...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862313/ https://www.ncbi.nlm.nih.gov/pubmed/27373736 http://dx.doi.org/10.1093/bib/bbw057 |
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author | Jaakkola, Maria K Seyednasrollah, Fatemeh Mehmood, Arfa Elo, Laura L |
author_facet | Jaakkola, Maria K Seyednasrollah, Fatemeh Mehmood, Arfa Elo, Laura L |
author_sort | Jaakkola, Maria K |
collection | PubMed |
description | We compared five statistical methods to detect differentially expressed genes between two distinct single-cell populations. Currently, it remains unclear whether differential expression methods developed originally for conventional bulk RNA-seq data can also be applied to single-cell RNA-seq data analysis. Our results in three diverse comparison settings showed marked differences between the different methods in terms of the number of detections as well as their sensitivity and specificity. They, however, did not reveal systematic benefits of the currently available single-cell-specific methods. Instead, our previously introduced reproducibility-optimization method showed good performance in all comparison settings without any single-cell-specific modifications. |
format | Online Article Text |
id | pubmed-5862313 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-58623132018-08-31 Comparison of methods to detect differentially expressed genes between single-cell populations Jaakkola, Maria K Seyednasrollah, Fatemeh Mehmood, Arfa Elo, Laura L Brief Bioinform Papers We compared five statistical methods to detect differentially expressed genes between two distinct single-cell populations. Currently, it remains unclear whether differential expression methods developed originally for conventional bulk RNA-seq data can also be applied to single-cell RNA-seq data analysis. Our results in three diverse comparison settings showed marked differences between the different methods in terms of the number of detections as well as their sensitivity and specificity. They, however, did not reveal systematic benefits of the currently available single-cell-specific methods. Instead, our previously introduced reproducibility-optimization method showed good performance in all comparison settings without any single-cell-specific modifications. Oxford University Press 2017-09 2016-07-02 /pmc/articles/PMC5862313/ /pubmed/27373736 http://dx.doi.org/10.1093/bib/bbw057 Text en © The Author 2016. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Papers Jaakkola, Maria K Seyednasrollah, Fatemeh Mehmood, Arfa Elo, Laura L Comparison of methods to detect differentially expressed genes between single-cell populations |
title | Comparison of methods to detect differentially expressed genes between single-cell populations |
title_full | Comparison of methods to detect differentially expressed genes between single-cell populations |
title_fullStr | Comparison of methods to detect differentially expressed genes between single-cell populations |
title_full_unstemmed | Comparison of methods to detect differentially expressed genes between single-cell populations |
title_short | Comparison of methods to detect differentially expressed genes between single-cell populations |
title_sort | comparison of methods to detect differentially expressed genes between single-cell populations |
topic | Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862313/ https://www.ncbi.nlm.nih.gov/pubmed/27373736 http://dx.doi.org/10.1093/bib/bbw057 |
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